diff --git a/.Rbuildignore b/.Rbuildignore
index 3c05a31..0da5d1c 100644
--- a/.Rbuildignore
+++ b/.Rbuildignore
@@ -15,3 +15,5 @@
^Makefile$
^make$
^\.githooks$
+^CITATION\.cff$
+^SKILLS\.md$
diff --git a/DESCRIPTION b/DESCRIPTION
index b9a2bdb..72d4539 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -9,7 +9,6 @@ Description: A Shiny application to help users explore and enjoy their 'omics da
License: MIT + file LICENSE
Encoding: UTF-8
Imports:
- devtools,
shiny,
shinydashboard,
tidyverse,
@@ -68,7 +67,9 @@ Imports:
openxlsx,
readr,
tibble,
- xml2
+ xml2,
+ dendextend,
+ rlang
Suggests:
DOSE,
testthat (>= 3.0.0),
@@ -78,12 +79,10 @@ Suggests:
arrow,
knitr,
rmarkdown,
- dendextend,
- rlang,
- withr
+ withr,
+ devtools
VignetteBuilder: knitr
Config/testthat/edition: 3
Remotes:
github::scverse/anndataR
-Config/roxygen2/version: 8.0.0
-RoxygenNote: 7.3.3
+Config/roxygen2/version: 8.1.1
diff --git a/NAMESPACE b/NAMESPACE
index 0b308a0..fa463ab 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -11,3 +11,6 @@ export(build_explore_h5ad)
export(exploreDE)
export(new_explore_dataset)
export(validate_explore_dataset)
+importFrom(R6,R6Class)
+importFrom(dplyr,"%>%")
+importFrom(rlang,.data)
diff --git a/NEWS.md b/NEWS.md
index c89795d..5d424ce 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -75,10 +75,12 @@
and a minimal Python writer) and `exploreDE-session-2.md` (session files).
- README, the bring-your-own-data vignette, and the AI skill now cover
writing files outside R, opening files from a link, and saving sessions.
+- The help pages of the `ExploreDataset*` classes describe every public method and its arguments.
## Removed
- The App Data tab (deprecated).
+- `devtools` as a dependency: installing exploreDE no longer installs it. `dendextend` and `rlang`, which the package code calls, move from Suggests to Imports.
# exploreDE 3.8.0
diff --git a/R/ExploreDataset.R b/R/ExploreDataset.R
index 98fe0a1..8078283 100644
--- a/R/ExploreDataset.R
+++ b/R/ExploreDataset.R
@@ -15,44 +15,74 @@ ExploreDataset <- R6::R6Class(
classname = "ExploreDataset",
public = list(
+ #' @description Always errors: the base class is abstract. Use [new_explore_dataset()] or a concrete subclass.
+ #' @param ... Ignored.
initialize = function(...) {
stop("ExploreDataset is abstract. ", "Use new_explore_dataset() or one of the concrete subclasses.")
},
# ---- identity (config-only) -------------------------------------------
+ #' @description Omics class from the config: `"genomics"` or `"proteomics"`.
omics_class = function() private$.config$omics_class,
+ #' @description Dataset type from the config, e.g. `"RNASeq"`, `"CountQC"`, `"CrisprCountQC"` or `"proteomics"`.
data_type = function() private$.config$data_type,
+ #' @description `TRUE` when the dataset has at least one contrast.
has_de = function() length(self$contrasts()) > 0L,
+ #' @description `TRUE` when the config lists at least one enrichment kind.
has_enrichment = function() {
length(private$.config$enrichment_kinds %||% character()) > 0L
},
+ #' @description Organism from the config, or `NA` when unknown.
organism = function() private$.config$organism %||% NA_character_,
+ #' @description Reference genome build from the config, or `NA` when unknown.
ref_build = function() private$.config$ref_build %||% NA_character_,
+ #' @description What a feature ID denotes, from the config, e.g. `"gene"`, `"isoform"`, `"protein"`,
+ #' `"peptide"`, `"phospho"` or `"guide"`.
feature_id_kind = function() private$.config$feature_id_kind,
+ #' @description Low-signal offset added to expression values before taking log2; from the config, default 10.
background_expression = function() {
private$.config$background_expression %||% 10
},
+ #' @description Short tag naming the storage backend (`"se"`, `"h5ad"` or `"parquet"`). Implemented by subclasses.
backend_kind = function() stop("not implemented"),
+ #' @description The underlying storage object. Implemented by subclasses.
backend = function() stop("not implemented"),
# ---- samples (samples() virtual; rest derived) ------------------------
+ #' @description Sample metadata as a data.frame, one row per sample, rownames are sample IDs.
+ #' Implemented by subclasses.
samples = function() stop("not implemented"),
+ #' @description Sample IDs: the rownames of `samples()`.
sample_ids = function() rownames(self$samples()),
+ #' @description Number of samples: the number of rows of `samples()`.
n_samples = function() nrow(self$samples()),
+ #' @description Names of the experimental factors from the config; empty when there are none.
factor_names = function() private$.config$factors %||% character(),
+ #' @description Levels of one experimental factor, from the config.
+ #' @param factor Factor name, one of `factor_names()`.
factor_levels = function(factor) {
private$.config$factor_levels[[factor]]
},
+ #' @description Name of the factor used as the primary sample grouping, from the config.
primary_grouping = function() private$.config$primary_grouping,
# NA when the dataset has no secondary grouping (e.g. proteomics, or
# SUSHI params with grouping2Name blank).
+ #' @description Name of the secondary grouping factor, or `NA` when there is none.
secondary_grouping = function() private$.config$secondary_grouping %||% NA_character_,
+ #' @description One column of `samples()`: the values of a factor, one per sample.
+ #' @param factor Column name in `samples()`, usually one of `factor_names()`.
sample_factor = function(factor) self$samples()[[factor]],
# ---- features (features() virtual; rest derived) ----------------------
+ #' @description Feature annotation as a data.frame, one row per feature, rownames are feature IDs, with a
+ #' `display_name` column. Implemented by subclasses.
features = function() stop("not implemented"),
+ #' @description Feature IDs: the rownames of `features()`.
feature_ids = function() rownames(self$features()),
+ #' @description Number of features: the number of rows of `features()`.
n_features = function() nrow(self$features()),
+ #' @description Display names of features, named by feature ID.
+ #' @param ids Feature IDs to look up; `NULL` (default) returns all features.
feature_display = function(ids = NULL) {
f <- self$features()
if (is.null(ids)) {
@@ -62,14 +92,23 @@ ExploreDataset <- R6::R6Class(
},
# ---- assays (assay_names + assay virtual; rest derived) ---------------
+ #' @description Canonical names of the assays this dataset provides. Implemented by subclasses.
assay_names = function() stop("not implemented"),
+ #' @description `TRUE` when `name` is one of `assay_names()`.
+ #' @param name Canonical assay name.
has_assay = function(name) name %in% self$assay_names(),
+ #' @description One assay as a features x samples matrix, optionally subset. Implemented by subclasses.
+ #' @param name Canonical assay name, one of `assay_names()`.
+ #' @param features Feature IDs (rows) to keep; `NULL` keeps all.
+ #' @param samples Sample IDs (columns) to keep; `NULL` keeps all.
assay = function(name, features = NULL, samples = NULL) {
stop("not implemented")
},
# Human-readable label for an assay (used by UI dropdowns).
# Subclass populates private$.config$assay_labels at build_config() time.
# Falls back to the canonical name if no label is registered.
+ #' @description Human-readable label for an assay, from the config; `name` itself when no label is registered.
+ #' @param name Canonical assay name.
assay_label = function(name) {
labels <- private$.config$assay_labels %||% list()
if (name %in% names(labels)) {
@@ -77,20 +116,34 @@ ExploreDataset <- R6::R6Class(
}
name
},
+ #' @description Canonical name of the raw assay, from the config.
raw_assay_name = function() private$.config$raw_assay_name,
+ #' @description Canonical name of the primary assay, from the config.
primary_assay_name = function() private$.config$primary_assay_name,
+ #' @description The raw assay: shortcut for `assay(raw_assay_name(), ...)`.
+ #' @param ... Passed to `assay()`: `features`, `samples`.
raw_assay = function(...) self$assay(self$raw_assay_name(), ...),
+ #' @description The primary assay: shortcut for `assay(primary_assay_name(), ...)`.
+ #' @param ... Passed to `assay()`: `features`, `samples`.
primary_assay = function(...) self$assay(self$primary_assay_name(), ...),
# ---- DE (de() virtual; rest config-only) ------------------------------
+ #' @description Names of the DE contrasts, from the config; empty when the dataset has no DE results.
contrasts = function() {
names(private$.config$contrast_meta) %||% character()
},
+ #' @description Name of the primary contrast, from the config; `NA` when there are no contrasts.
primary_contrast = function() private$.config$primary_contrast,
+ #' @description DE result table for one contrast, as a data.frame. Implemented by subclasses.
+ #' @param contrast Contrast name, one of `contrasts()`.
de = function(contrast) stop("not implemented"),
+ #' @description DE result tables of all contrasts, as a list named by contrast.
de_all = function() {
setNames(lapply(self$contrasts(), self$de), self$contrasts())
},
+ #' @description Metadata list of one contrast from the config: test and reference group, factor, method,
+ #' thresholds. Errors on an unknown contrast.
+ #' @param contrast Contrast name, one of `contrasts()`.
contrast_meta = function(contrast) {
stopifnot(contrast %in% self$contrasts())
private$.config$contrast_meta[[contrast]]
@@ -100,6 +153,8 @@ ExploreDataset <- R6::R6Class(
# _RNASeq$.build_config; supplied directly by prolfqua for proteomics),
# so this helper just validates and returns it. Modules wanting prose
# ("diff vs undiff") for plot titles can `gsub("_vs_", " vs ", x)`.
+ #' @description Display label of a contrast: currently the contrast name itself. Errors on an unknown contrast.
+ #' @param contrast Contrast name, one of `contrasts()`.
contrast_label = function(contrast) {
stopifnot(contrast %in% self$contrasts())
contrast
@@ -108,11 +163,15 @@ ExploreDataset <- R6::R6Class(
# Extra DE columns to surface for display only (beyond log2Ratio/pValue/fdr)
# — e.g. SAINTexpress's SaintScore. Default none; backends declaring a
# mapping (H5AD) override via config. Names are also the DE-table labels.
+ #' @description Names of extra DE columns shown for display only (e.g. `SaintScore`), from the config;
+ #' empty by default.
de_display_extras = function() private$.config$de_display_extras %||% character(),
# Does any contrast carry a usable RAW p-value? FALSE for FDR-only producers
# (SAINTexpress), which the p-value-type selectors use to degrade to
# FDR-only rather than plotting all-NA -log10(pValue).
+ #' @description `TRUE` when the DE table of at least one contrast has a non-missing raw `pValue`;
+ #' `FALSE` for FDR-only producers such as SAINTexpress.
has_pvalue = function() {
if (!self$has_de()) {
return(FALSE)
@@ -127,10 +186,18 @@ ExploreDataset <- R6::R6Class(
},
# ---- enrichment (all virtual except enrichment_kinds) -----------------
+ #' @description Enrichment kinds available, from the config: any of `"ora"` and `"gsea"`.
enrichment_kinds = function() {
private$.config$enrichment_kinds %||% character()
},
+ #' @description Enrichment results of one contrast and kind, as a flat named list of clusterProfiler results.
+ #' Implemented by subclasses.
+ #' @param contrast Contrast name, one of `contrasts()`.
+ #' @param kind `"ora"` or `"gsea"`.
enrichment = function(contrast, kind) stop("not implemented"),
+ #' @description Inputs for enrichment of one contrast: `list(seq_anno, ranked_l2fc, selections)`.
+ #' Implemented by subclasses.
+ #' @param contrast Contrast name, one of `contrasts()`.
enrichment_input = function(contrast) stop("not implemented"),
# Tidy enrichment as a plain data.frame — the form that does NOT require
@@ -142,6 +209,10 @@ ExploreDataset <- R6::R6Class(
# file ever written, including those with no uns$enrichment block. Backends
# holding a stored tidy mirror should override and prefer it.
# See plans/exploredelight/enrichment_detach_plan.md.
+ #' @description Enrichment results of one contrast and kind as one tidy data.frame, derived from
+ #' `enrichment()`; an empty data.frame when there are none.
+ #' @param contrast Contrast name, one of `contrasts()`.
+ #' @param kind `"ora"` or `"gsea"`.
enrichment_table = function(contrast, kind) {
objs <- self$enrichment(contrast, kind)
if (!length(objs)) {
@@ -166,12 +237,18 @@ ExploreDataset <- R6::R6Class(
# were derived live and nothing was filtered. Callers that let a user raise
# a GO threshold need this: without it an absent row is ambiguous between
# "cut by the writer", "not significant" and "never run".
+ #' @description The `p.adjust` cut-off applied to the stored enrichment tables, from the config;
+ #' `NA` when none was applied.
enrichment_filter = function() {
private$.config$enrichment_filter %||% NA_real_
},
# ---- domain extras (config-only) --------------------------------------
+ #' @description Named character vector mapping sgRNA IDs to gene names (CRISPR datasets); `NULL` otherwise.
sgrna_to_gene = function() private$.config$sgrna_to_gene,
+ #' @description Choices and lookup for the proteomics feature picker, `list(choices, lookup)`; `NULL` when the
+ #' dataset has none.
+ #' @param kind `"gene"` (default) or `"protein"`.
proteomics_choices = function(kind = c("gene", "protein")) {
kind <- match.arg(kind)
private$.config$proteomics[[kind]]
@@ -183,6 +260,8 @@ ExploreDataset <- R6::R6Class(
# the GO BP / GO MF / GO CC columns in features(), so works for any
# backend. Returns character(0) when those columns are absent (proteomics,
# CountQC without GO annotations).
+ #' @description GO terms named in the `GO BP`, `GO MF` and `GO CC` columns of `features()`, as
+ #' `"GO:ID term name"` strings; empty when those columns are absent.
all_pathways = function() {
f <- self$features()
go_cols <- intersect(c("GO BP", "GO MF", "GO CC"), colnames(f))
@@ -209,9 +288,13 @@ ExploreDataset <- R6::R6Class(
},
# ---- provenance --------------------------------------------------------
+ #' @description Provenance list from the config: backend kind, schema version and build time.
source = function() private$.config$source,
# ---- lifecycle ---------------------------------------------------------
+ #' @description Print a summary of the dataset (type, dimensions, factors, contrasts, assays, enrichment)
+ #' and return the object invisibly.
+ #' @param ... Ignored.
print = function(...) {
cat("<", class(self)[1], " (", self$backend_kind(), ")>\n", sep = "")
cat(" data_type: ", self$data_type(), "\n", sep = "")
diff --git a/R/ExploreDatasetH5AD.R b/R/ExploreDatasetH5AD.R
index 9ecdb4a..5c0a3b0 100644
--- a/R/ExploreDatasetH5AD.R
+++ b/R/ExploreDatasetH5AD.R
@@ -112,6 +112,10 @@ ExploreDatasetH5AD <- R6::R6Class(
inherit = ExploreDataset,
public = list(
+ #' @description Read a canonical `.h5ad` or take a live AnnData, build the config from it unless one is given,
+ #' and prepare the feature and DE tables.
+ #' @param input An `anndataR` AnnData object, or a path to an existing `.h5ad` file.
+ #' @param config Optional pre-built config list; built from the AnnData when `NULL`.
initialize = function(input, config = NULL) {
adata <- if (inherits(input, "AbstractAnnData")) {
input
@@ -131,11 +135,16 @@ ExploreDatasetH5AD <- R6::R6Class(
invisible(self)
},
+ #' @description The AnnData parts read at construction, as `list(obs, var, layers, varm, uns)` of plain R
+ #' objects.
backend = function() {
list(obs = private$.obs, var = private$.var, layers = private$.layers, varm = private$.varm, uns = private$.uns)
},
+ #' @description Returns `"h5ad"`.
backend_kind = function() "h5ad",
+ #' @description Sample metadata from `obs`, with the `factor_` prefix stripped from column names and a `Name`
+ #' column added when missing.
samples = function() {
cd <- private$.obs
colnames(cd) <- .h5ad_strip_factor(colnames(cd))
@@ -153,13 +162,20 @@ ExploreDatasetH5AD <- R6::R6Class(
cd
},
+ #' @description Feature annotation from `var`, with `feature_id` and `display_name` columns, ordered by the
+ #' p-value of the primary contrast.
features = function() private$.features_df,
+ #' @description DE table of one contrast from `varm`, with the legacy aliases `log2Ratio`, `pValue` and `fdr`
+ #' added; an empty data.frame when the slot is missing. Errors on an unknown contrast.
+ #' @param contrast Contrast name, one of `contrasts()`.
de = function(contrast) {
stopifnot(contrast %in% self$contrasts())
private$.de_dfs[[contrast]] %||% data.frame()
},
+ #' @description Canonical assay names from the config's assay map whose layer exists; computed assays are
+ #' always included.
assay_names = function() {
keys <- names(private$.config$assay_map %||% list())
keys[vapply(
@@ -172,6 +188,11 @@ ExploreDatasetH5AD <- R6::R6Class(
)]
},
+ #' @description One assay as a features x samples matrix (the layer transposed); `normalised`,
+ #' `normalised_log2`, `vst`, `fpkm` and `tpm` are computed when the config maps them to no layer.
+ #' @param name Canonical assay name, one of `assay_names()`.
+ #' @param features Feature IDs (rows) to keep; `NULL` keeps all.
+ #' @param samples Sample IDs (columns) to keep; `NULL` keeps all.
assay = function(name, features = NULL, samples = NULL) {
layer_key <- private$.config$assay_map[[name]]
m <- if (!is.null(layer_key)) {
@@ -199,6 +220,10 @@ ExploreDatasetH5AD <- R6::R6Class(
m
},
+ #' @description Enrichment results of one contrast and kind: decoded from the serialised objects in older files,
+ #' otherwise rebuilt from `uns$enrichment` and `uns$enrichment_support`.
+ #' @param contrast Contrast name, one of `contrasts()`.
+ #' @param kind `"ora"` or `"gsea"`.
enrichment = function(contrast, kind) {
stopifnot(kind %in% c("ora", "gsea"))
stopifnot(contrast %in% self$contrasts())
@@ -226,6 +251,10 @@ ExploreDatasetH5AD <- R6::R6Class(
# Prefer the stored tidy mirror; fall back to the base class, which derives
# it from the native objects. So a new file costs no decode at all, and an
# old one still works.
+ #' @description Tidy enrichment table of one contrast and kind: the table stored in `uns$enrichment` when
+ #' present, otherwise derived from `enrichment()` as in the base class.
+ #' @param contrast Contrast name, one of `contrasts()`.
+ #' @param kind `"ora"` or `"gsea"`.
enrichment_table = function(contrast, kind) {
stopifnot(kind %in% c("ora", "gsea"))
slot <- sub("^de_", "", private$.contrast_slot[[contrast]] %||% contrast)
@@ -238,6 +267,9 @@ ExploreDatasetH5AD <- R6::R6Class(
# Canonical spec drops enrichInput; reconstruct on demand from varm + var
# so the (accessor-migrated) pathway modules have what they need.
+ #' @description Enrichment inputs rebuilt from the DE table: `features()`, log2 fold changes sorted decreasing,
+ #' and up/down feature selections at the contrast's FDR and log2FC thresholds.
+ #' @param contrast Contrast name, one of `contrasts()`.
enrichment_input = function(contrast) {
de <- tryCatch(self$de(contrast), error = function(e) NULL)
if (is.null(de) || !nrow(de)) {
diff --git a/R/ExploreDatasetParquet.R b/R/ExploreDatasetParquet.R
index 51ba486..d153638 100644
--- a/R/ExploreDatasetParquet.R
+++ b/R/ExploreDatasetParquet.R
@@ -117,6 +117,10 @@ ExploreDatasetParquet <- R6::R6Class(
inherit = ExploreDatasetH5AD,
public = list(
+ #' @description Read the parquet directory (manifest, obs, var, layers, varm, uns), build the config unless one
+ #' is given, prepare the feature and DE tables, and warn when the source `.h5ad` has changed since export.
+ #' @param input Path to the parquet directory.
+ #' @param config Optional pre-built config list; derived from `uns.json` when omitted.
initialize = function(input, config = NULL) {
if (!is.character(input) || length(input) != 1L || !dir.exists(input)) {
stop("ExploreDatasetParquet: input must be a path to a parquet directory")
@@ -170,6 +174,7 @@ ExploreDatasetParquet <- R6::R6Class(
invisible(self)
},
+ #' @description Returns `"parquet"`.
backend_kind = function() "parquet",
# Hydrate-then-delegate. The payloads live in their own files so that
@@ -177,22 +182,31 @@ ExploreDatasetParquet <- R6::R6Class(
# 13 MB of a 29 MB export). The first call for a contrast pulls the blobs
# in, after which the inherited implementation runs against exactly the
# structure it expects — no forked decode logic.
+ #' @description Enrichment results of one contrast and kind: reads the contrast's enrichment payload files on
+ #' first use, then defers to the `.h5ad` backend's implementation.
+ #' @param contrast Contrast name, one of `contrasts()`.
+ #' @param kind `"ora"` or `"gsea"`.
enrichment = function(contrast, kind) {
private$.hydrate_enrichment(contrast)
super$enrichment(contrast, kind)
},
# The manifest as written, for diagnostics.
+ #' @description The parsed `manifest.json` of the parquet directory.
manifest = function() private$.manifest,
# Where the Rust process put the files. Useful for diagnostics and for the
# app to clean up its temp dir on exit.
+ #' @description Path of the parquet directory.
source_dir = function() private$.dir,
# Full content check against the source .h5ad, as opposed to the cheap
# size/mtime comparison done at load. Returns TRUE when the recorded md5
# still matches, FALSE when it does not, and NA when there is nothing to
# check against (a live AnnData was exported, or the source has moved).
+ #' @description Compare the md5 of the source `.h5ad` with the one recorded in the manifest: `TRUE` when it
+ #' matches, `FALSE` when not, `NA` when there is nothing to check against.
+ #' @param path Path to the source `.h5ad`; `NULL` (default) uses the path recorded in the manifest.
verify_source = function(path = NULL) {
src <- private$.manifest$source %||% list()
p <- path %||% src$path
@@ -207,6 +221,7 @@ ExploreDatasetParquet <- R6::R6Class(
# the package is there (this class also runs on the cluster, under test)
# and an empty vector when it is not, which is what the callers already
# treat as "this dataset has no GO annotation".
+ #' @description GO terms as in the base class, but an empty vector when clusterProfiler is not installed.
all_pathways = function() {
if (!requireNamespace("clusterProfiler", quietly = TRUE)) {
return(character(0))
diff --git a/R/ExploreDatasetSE.R b/R/ExploreDatasetSE.R
index df507e9..190c92c 100644
--- a/R/ExploreDatasetSE.R
+++ b/R/ExploreDatasetSE.R
@@ -20,6 +20,10 @@ ExploreDatasetSE <- R6::R6Class(
inherit = ExploreDataset,
public = list(
+ #' @description Wrap a `SummarizedExperiment`: store it, build the config from it unless one is given, and
+ #' prepare the feature and DE tables.
+ #' @param se A `SummarizedExperiment`.
+ #' @param config Optional pre-built config list; built from `se` by the subclass when `NULL`.
initialize = function(se, config = NULL) {
stopifnot(inherits(se, "SummarizedExperiment"))
private$.se <- se
@@ -28,7 +32,9 @@ ExploreDatasetSE <- R6::R6Class(
invisible(self)
},
+ #' @description The wrapped `SummarizedExperiment`.
backend = function() private$.se,
+ #' @description Returns `"se"`.
backend_kind = function() "se",
# samples(): uniform colData read. SUSHI's `[Factor]` suffix is stripped
@@ -39,6 +45,8 @@ ExploreDatasetSE <- R6::R6Class(
# A `Name` column is added matching the legacy converters: factor-typed
# for genomics, plain character for proteomics. Rownames are colnames(se)
# where available, else cd$Name / cd$name fallback.
+ #' @description Sample metadata from `colData()`, with the SUSHI ` [Factor]` suffix stripped from column names,
+ #' rownames set to sample IDs, and a `Name` column added.
samples = function() {
cd <- data.frame(SummarizedExperiment::colData(private$.se), check.names = FALSE, stringsAsFactors = FALSE)
colnames(cd) <- gsub(" \\[.*", "", colnames(cd))
@@ -85,13 +93,19 @@ ExploreDatasetSE <- R6::R6Class(
cd
},
+ #' @description Feature annotation table, prepared from `rowData()` by the subclass.
features = function() private$.features_df,
+ #' @description DE table of one contrast, prepared from `rowData()` by the subclass; an empty data.frame when
+ #' none was prepared. Errors on an unknown contrast.
+ #' @param contrast Contrast name, one of `contrasts()`.
de = function(contrast) {
stopifnot(contrast %in% self$contrasts())
private$.de_dfs[[contrast]] %||% data.frame()
},
+ #' @description Canonical assay names from the config's assay map whose SE assay exists; computed assays are
+ #' always included.
assay_names = function() {
backend_keys <- SummarizedExperiment::assayNames(private$.se)
keys <- names(private$.config$assay_map %||% list())
@@ -105,6 +119,11 @@ ExploreDatasetSE <- R6::R6Class(
)]
},
+ #' @description One assay as a features x samples matrix with rows renamed to feature IDs; `normalised_log2`,
+ #' `vst`, `fpkm` and `tpm` are computed when the config maps them to no SE assay.
+ #' @param name Canonical assay name, one of `assay_names()`.
+ #' @param features Feature IDs (rows) to keep; `NULL` keeps all.
+ #' @param samples Sample IDs (columns) to keep; `NULL` keeps all.
assay = function(name, features = NULL, samples = NULL) {
v <- private$.config$assay_map[[name]]
m <- if (!is.null(v)) {
@@ -140,6 +159,10 @@ ExploreDatasetSE <- R6::R6Class(
m
},
+ #' @description Enrichment results of one kind, read from `metadata(se)` and flattened to a named list; an empty
+ #' list when absent. `contrast` is not used.
+ #' @param contrast Contrast name; not used by this backend.
+ #' @param kind `"ora"` or `"gsea"`.
enrichment = function(contrast, kind) {
stopifnot(kind %in% c("ora", "gsea"))
loc <- private$.config$enrichment_locator[[kind]]$se
@@ -153,6 +176,9 @@ ExploreDatasetSE <- R6::R6Class(
eds_flatten_cp_results(obj)
},
+ #' @description Enrichment inputs read from `metadata(se)$enrichInput`, with `NULL` fields and no selections when
+ #' absent. `contrast` is not used.
+ #' @param contrast Contrast name; not used by this backend.
enrichment_input = function(contrast) {
ei <- S4Vectors::metadata(private$.se)$enrichInput
if (is.null(ei)) {
diff --git a/R/banana_mode.R b/R/banana_mode.R
index dece314..c197aca 100644
--- a/R/banana_mode.R
+++ b/R/banana_mode.R
@@ -311,7 +311,7 @@ banana_layer <- function(data, x, y, fdr_col, facet_col = "Feature", px = 16L) {
d$bx <- x
ggtext::geom_richtext(
data = d,
- mapping = ggplot2::aes(x = bx, y = by, label = md),
+ mapping = ggplot2::aes(x = .data$bx, y = .data$by, label = .data$md),
vjust = -0.1,
inherit.aes = FALSE,
fill = NA,
diff --git a/R/build_explore_h5ad.R b/R/build_explore_h5ad.R
index 64df05d..ee22eac 100644
--- a/R/build_explore_h5ad.R
+++ b/R/build_explore_h5ad.R
@@ -389,7 +389,7 @@
# feature_level: detection-with-override, then level-aware feature_id.
level <- .resolve_feature_level(omics_type, rd, feature_level)
fid <- .build_fid_for_level(level, base_ids, gid, sym, rd, id_col = explicit_id_col)
- id2fid <- setNames(fid, base_ids) # user identifiers -> canonical fid
+ id2fid <- stats::setNames(fid, base_ids) # user identifiers -> canonical fid
# -- obs (samples) : factors get "factor_" prefix; others carried plain -----
obs <- .as_df_keep_names(coldata)
@@ -655,19 +655,19 @@
for (rn in names(results)) {
obj <- results[[rn]]
if (is.data.frame(obj)) {
- enr_tidy[[slot]] <- c(enr_tidy[[slot]], setNames(list(obj), rn))
+ enr_tidy[[slot]] <- c(enr_tidy[[slot]], stats::setNames(list(obj), rn))
} else if (!.contains_native_cp(obj)) {
tidy <- .enr_tidy_from_native(obj, method = rn)
if (!is.null(tidy)) {
- enr_tidy[[slot]] <- c(enr_tidy[[slot]], setNames(list(tidy), rn))
+ enr_tidy[[slot]] <- c(enr_tidy[[slot]], stats::setNames(list(tidy), rn))
}
} else {
tidy <- .enr_tidy_from_native(obj, method = rn, padj_max = .padj_max_for(enrichment_padj_max, rn))
if (!is.null(tidy)) {
- enr_tidy[[slot]] <- c(enr_tidy[[slot]], setNames(list(tidy), rn))
+ enr_tidy[[slot]] <- c(enr_tidy[[slot]], stats::setNames(list(tidy), rn))
sup <- .enr_support_from_native(obj, tidy)
if (!is.null(sup)) {
- enr_support[[slot]] <- c(enr_support[[slot]], setNames(list(sup), rn))
+ enr_support[[slot]] <- c(enr_support[[slot]], stats::setNames(list(sup), rn))
}
}
}
diff --git a/R/downloadHelpers.R b/R/downloadHelpers.R
index 732fe42..00a0ca7 100644
--- a/R/downloadHelpers.R
+++ b/R/downloadHelpers.R
@@ -58,14 +58,14 @@ export_plot_standard <- function(plot_object, filename, format = "pdf", dpi = 30
# Greek in rich level labels is rewritten to the Symbol font for it.
if (format == "pdf") {
plot_object <- prepare_plot_for_pdf(plot_object)
- pdf(file = filename, width = width, height = height)
+ grDevices::pdf(file = filename, width = width, height = height)
} else if (format == "svg") {
- svg(file = filename, width = width, height = height)
+ grDevices::svg(file = filename, width = width, height = height)
} else if (format == "png") {
- png(filename = filename, width = width, height = height, units = "in", res = as.numeric(dpi))
+ grDevices::png(filename = filename, width = width, height = height, units = "in", res = as.numeric(dpi))
} else {
warning("Unknown format '", format, "'. Defaulting to PDF.")
- pdf(file = filename, width = width, height = height)
+ grDevices::pdf(file = filename, width = width, height = height)
}
# Print/Draw the plot
@@ -82,7 +82,7 @@ export_plot_standard <- function(plot_object, filename, format = "pdf", dpi = 30
},
finally = {
# Ensure device is closed even if printing fails
- dev.off()
+ grDevices::dev.off()
}
)
}
diff --git a/R/exploreDE-package.R b/R/exploreDE-package.R
new file mode 100644
index 0000000..a21f0a8
--- /dev/null
+++ b/R/exploreDE-package.R
@@ -0,0 +1,4 @@
+#' @importFrom dplyr %>%
+#' @importFrom R6 R6Class
+#' @importFrom rlang .data
+NULL
diff --git a/R/helperFunctions.R b/R/helperFunctions.R
index 9a7077c..649c449 100644
--- a/R/helperFunctions.R
+++ b/R/helperFunctions.R
@@ -346,8 +346,8 @@ dataSummary <- function(data, varname, groupnames) {
summary_func <- function(x, col) {
c(
mean = mean(x[[col]], na.rm = TRUE),
- sd = sd(x[[col]], na.rm = TRUE),
- se = sd(x[[col]], na.rm = TRUE) / sqrt(sum(!is.na(x[[col]])))
+ sd = stats::sd(x[[col]], na.rm = TRUE),
+ se = stats::sd(x[[col]], na.rm = TRUE) / sqrt(sum(!is.na(x[[col]])))
)
}
data_sum <- plyr::ddply(
@@ -373,8 +373,8 @@ dataSummary <- function(data, varname, groupnames) {
#' @return Character vector of rownames for the top features
#' @noRd
select_genes_by_sd <- function(counts, top_n = 2000) {
- gene_sds <- apply(counts, 1, sd, na.rm = TRUE)
- top_genes <- names(head(sort(gene_sds, decreasing = TRUE), n = top_n))
+ gene_sds <- apply(counts, 1, stats::sd, na.rm = TRUE)
+ top_genes <- names(utils::head(sort(gene_sds, decreasing = TRUE), n = top_n))
return(top_genes)
}
@@ -395,6 +395,9 @@ bind_to_scope <- function(fn, env = parent.frame()) {
fn
}
+# Session objects the bound helpers below read from the server scope
+utils::globalVariables(c("eds", "input", "seqAnnoReactive"))
+
# =============================================================================
# Feature bucket API (used by server-featureBucket.R, bound there with bind_to_scope())
# NOTE: bucket_add/remove/clear and resolve_features reference the Shiny
@@ -421,11 +424,11 @@ bucket_add <- function(new_features, source = "unknown") {
valid_ids <- c(valid_ids, unique(sg))
}
valid <- new_features[new_features %in% valid_ids & new_features != ""]
- current <- isolate(featureBucket$features)
+ current <- shiny::isolate(featureBucket$features)
to_add <- setdiff(valid, current)
if (length(to_add) > 0) {
featureBucket$features <- c(current, to_add)
- featureBucket$version <- isolate(featureBucket$version) + 1L
+ featureBucket$version <- shiny::isolate(featureBucket$version) + 1L
}
}
@@ -435,11 +438,11 @@ bucket_add <- function(new_features, source = "unknown") {
#' @param source Label for telemetry
#' @noRd
bucket_remove <- function(to_remove, source = "unknown") {
- current <- isolate(featureBucket$features)
+ current <- shiny::isolate(featureBucket$features)
remaining <- current[!current %in% to_remove]
if (length(remaining) != length(current)) {
featureBucket$features <- remaining
- featureBucket$version <- isolate(featureBucket$version) + 1L
+ featureBucket$version <- shiny::isolate(featureBucket$version) + 1L
}
}
@@ -449,7 +452,7 @@ bucket_remove <- function(to_remove, source = "unknown") {
#' @noRd
bucket_clear <- function(source = "unknown") {
featureBucket$features <- character(0)
- featureBucket$version <- isolate(featureBucket$version) + 1L
+ featureBucket$version <- shiny::isolate(featureBucket$version) + 1L
}
#' parse_gene_text
@@ -499,13 +502,13 @@ resolve_features <- function(input_genes, search_mode = "feature_id") {
#' @param title_suffix String appended to heatmap title
#' @noRd
make_rep_heatmap <- function(data, title_suffix = "") {
- req(data)
+ shiny::req(data)
# Prepare annotations
ha_top <- NULL
ha_left <- NULL
- row_names_gp <- gpar(fontsize = input$replicabilityTextSize)
- column_names_gp <- gpar(fontsize = input$replicabilityTextSize)
+ row_names_gp <- grid::gpar(fontsize = input$replicabilityTextSize)
+ column_names_gp <- grid::gpar(fontsize = input$replicabilityTextSize)
if (!is.null(input$replicabilityFactors)) {
dataset <- data$dataset
@@ -522,14 +525,14 @@ make_rep_heatmap <- function(data, title_suffix = "") {
if (is.null(col_input)) {
return("#808080FF")
}
- tryCatch(paste0(col2hex(col_input), "FF"), error = function(e) "#808080FF")
+ tryCatch(paste0(gplots::col2hex(col_input), "FF"), error = function(e) "#808080FF")
},
character(1)
)
names(colors) <- levs
return(colors)
}) %>%
- setNames(input$replicabilityFactors)
+ stats::setNames(input$replicabilityFactors)
# Color labels based on the first selected factor
factor_col <- input$replicabilityFactors[1]
@@ -541,7 +544,7 @@ make_rep_heatmap <- function(data, title_suffix = "") {
if (is.null(col_input)) {
return("#808080FF")
}
- tryCatch(paste0(col2hex(col_input), "FF"), error = function(e) "#808080FF")
+ tryCatch(paste0(gplots::col2hex(col_input), "FF"), error = function(e) "#808080FF")
},
character(1)
)
@@ -549,8 +552,8 @@ make_rep_heatmap <- function(data, title_suffix = "") {
sample_colors <- colors[as.character(dataset[[factor_col]])]
names(sample_colors) <- dataset$Name
- row_names_gp <- gpar(fontsize = input$replicabilityTextSize, col = sample_colors)
- column_names_gp <- gpar(fontsize = input$replicabilityTextSize, col = sample_colors)
+ row_names_gp <- grid::gpar(fontsize = input$replicabilityTextSize, col = sample_colors)
+ column_names_gp <- grid::gpar(fontsize = input$replicabilityTextSize, col = sample_colors)
anno_df <- dataset[, input$replicabilityFactors, drop = FALSE]
@@ -567,15 +570,15 @@ make_rep_heatmap <- function(data, title_suffix = "") {
levs <- names(colourList[[f]])
list(at = levs, labels = unname(level_labels(input, f, levs, mode = "plain")))
}) %>%
- setNames(input$replicabilityFactors)
+ stats::setNames(input$replicabilityFactors)
- ha_top <- HeatmapAnnotation(
+ ha_top <- ComplexHeatmap::HeatmapAnnotation(
df = anno_df,
col = colourList,
show_legend = !repRich,
annotation_legend_param = annoLegendParam,
- annotation_name_gp = gpar(fontsize = input$replicabilityTextSize, fontface = "bold"),
- gp = gpar(col = input$replicabilityBorderColor1, lwd = input$replicabilityBorderSize1 / 10)
+ annotation_name_gp = grid::gpar(fontsize = input$replicabilityTextSize, fontface = "bold"),
+ gp = grid::gpar(col = input$replicabilityBorderColor1, lwd = input$replicabilityBorderSize1 / 10)
)
if (repRich) {
attr(ha_top, "rich_legends") <- lapply(input$replicabilityFactors, function(f) {
@@ -583,18 +586,18 @@ make_rep_heatmap <- function(data, title_suffix = "") {
title = f,
labels = level_labels(input, f, names(colourList[[f]]), force_rich = TRUE),
fill = colourList[[f]],
- title_gp = gpar(fontsize = input$replicabilityTextSize, fontface = "bold"),
- labels_gp = gpar(fontsize = input$replicabilityTextSize)
+ title_gp = grid::gpar(fontsize = input$replicabilityTextSize, fontface = "bold"),
+ labels_gp = grid::gpar(fontsize = input$replicabilityTextSize)
)
})
}
- ha_left <- rowAnnotation(
+ ha_left <- ComplexHeatmap::rowAnnotation(
df = anno_df,
col = colourList,
show_legend = FALSE,
- annotation_name_gp = gpar(fontsize = input$replicabilityTextSize, fontface = "bold"),
- gp = gpar(col = input$replicabilityBorderColor1, lwd = input$replicabilityBorderSize1 / 10)
+ annotation_name_gp = grid::gpar(fontsize = input$replicabilityTextSize, fontface = "bold"),
+ gp = grid::gpar(col = input$replicabilityBorderColor1, lwd = input$replicabilityBorderSize1 / 10)
)
}
@@ -603,15 +606,15 @@ make_rep_heatmap <- function(data, title_suffix = "") {
# Determine color scheme - use palette if selected, otherwise use manual colors
if (!is.null(input$replicabilityPalette) && input$replicabilityPalette != "None") {
- palette_colours <- brewer.pal(9, input$replicabilityPalette)
+ palette_colours <- RColorBrewer::brewer.pal(9, input$replicabilityPalette)
selected_colours <- palette_colours[c(1, 5, 9)]
if (input$replicabilityPaletteRev) {
- heatmap_colours <- colorRamp2(at, selected_colours)
+ heatmap_colours <- circlize::colorRamp2(at, selected_colours)
} else {
- heatmap_colours <- colorRamp2(at, rev(selected_colours))
+ heatmap_colours <- circlize::colorRamp2(at, rev(selected_colours))
}
} else {
- heatmap_colours <- colorRamp2(
+ heatmap_colours <- circlize::colorRamp2(
at,
c(input$replicabilityColorLow, input$replicabilityColorMid, input$replicabilityColorHigh)
)
@@ -627,16 +630,16 @@ make_rep_heatmap <- function(data, title_suffix = "") {
show_column_names = input$replicabilityShowNames,
row_names_gp = row_names_gp,
column_names_gp = column_names_gp,
- heatmap_legend_param = list(title_gp = gpar(fontsize = input$replicabilityTextSize, fontface = "bold")),
- rect_gp = gpar(col = input$replicabilityBorderColor2, lwd = input$replicabilityBorderSize2 / 10),
+ heatmap_legend_param = list(title_gp = grid::gpar(fontsize = input$replicabilityTextSize, fontface = "bold")),
+ rect_gp = grid::gpar(col = input$replicabilityBorderColor2, lwd = input$replicabilityBorderSize2 / 10),
column_title = paste0("Correlation Heatmap: ", title_suffix),
- column_title_gp = gpar(fontsize = input$replicabilityTextSize + 2, fontface = "bold")
+ column_title_gp = grid::gpar(fontsize = input$replicabilityTextSize + 2, fontface = "bold")
)
draw_heatmap(
hm,
merge_legend = TRUE,
- padding = unit(c(10, 10, 10, 10), "mm"),
+ padding = grid::unit(c(10, 10, 10, 10), "mm"),
legend_dx = input$replicabilityLegendDX,
legend_dy = input$replicabilityLegendDY
)
@@ -648,8 +651,8 @@ make_rep_heatmap <- function(data, title_suffix = "") {
#' @param title_suffix String appended to title
#' @noRd
make_rep_dendrogram <- function(data, title_suffix = "") {
- req(data)
- dend <- as.dendrogram(data$hclust)
+ shiny::req(data)
+ dend <- stats::as.dendrogram(data$hclust)
if (!is.null(input$replicabilityFactors)) {
dataset <- data$dataset
@@ -662,14 +665,14 @@ make_rep_dendrogram <- function(data, title_suffix = "") {
if (is.null(col_input)) {
return("#808080FF")
}
- tryCatch(paste0(col2hex(col_input), "FF"), error = function(e) "#808080FF")
+ tryCatch(paste0(gplots::col2hex(col_input), "FF"), error = function(e) "#808080FF")
},
character(1)
)
sample_colors <- colors[as.character(dataset[[factor_col]])]
names(sample_colors) <- dataset$Name
- labels_colors(dend) <- sample_colors[labels(dend)]
+ dendextend::labels_colors(dend) <- sample_colors[labels(dend)]
colors_mat <- as.data.frame(dataset[, input$replicabilityFactors, drop = FALSE])
for (f in input$replicabilityFactors) {
@@ -680,7 +683,7 @@ make_rep_dendrogram <- function(data, title_suffix = "") {
if (is.null(col_input)) {
return("#808080FF")
}
- tryCatch(paste0(col2hex(col_input), "FF"), error = function(e) "#808080FF")
+ tryCatch(paste0(gplots::col2hex(col_input), "FF"), error = function(e) "#808080FF")
},
character(1)
)
@@ -688,7 +691,7 @@ make_rep_dendrogram <- function(data, title_suffix = "") {
colors_mat <- colors_mat[match(labels(dend), dataset$Name), , drop = FALSE]
}
- par(mar = c(20, 8, 6, 4))
+ graphics::par(mar = c(20, 8, 6, 4))
plot(
dend,
main = paste0(
@@ -705,7 +708,7 @@ make_rep_dendrogram <- function(data, title_suffix = "") {
)
if (!is.null(input$replicabilityFactors)) {
- colored_bars(colors = colors_mat, dend = dend, sort_by_labels_order = FALSE)
+ dendextend::colored_bars(colors = colors_mat, dend = dend, sort_by_labels_order = FALSE)
}
}
@@ -906,7 +909,7 @@ getPackageVersions <- function(packages) {
versions <- sapply(packages, function(pkg) {
tryCatch(
{
- as.character(packageVersion(pkg))
+ as.character(utils::packageVersion(pkg))
},
error = function(e) {
"version unavailable"
@@ -992,7 +995,7 @@ generateMethodsText <- function(param, aligner, de_method, fastp_version, pkg_ve
if (!is.null(se)) {
tryCatch(
{
- lib_sizes <- colSums(assay(se, "counts"))
+ lib_sizes <- colSums(SummarizedExperiment::assay(se, "counts"))
min_size <- round(min(lib_sizes) / 1e6, 1)
max_size <- round(max(lib_sizes) / 1e6, 1)
final_reads_info <- paste0(
@@ -1195,7 +1198,7 @@ generateMethodsText <- function(param, aligner, de_method, fastp_version, pkg_ve
#' @noRd
calculate_pca <- function(counts, center = TRUE, scale = FALSE) {
# Remove samples with missing values
- completeCases <- complete.cases(counts)
+ completeCases <- stats::complete.cases(counts)
counts_clean <- counts[completeCases, ]
if (nrow(counts_clean) < 3 || ncol(counts_clean) < 3) {
@@ -1205,7 +1208,7 @@ calculate_pca <- function(counts, center = TRUE, scale = FALSE) {
# Run PCA
pca_result <- tryCatch(
{
- prcomp(counts_clean, center = center, scale. = scale)
+ stats::prcomp(counts_clean, center = center, scale. = scale)
},
error = function(e) {
return(NULL)
@@ -1238,7 +1241,7 @@ calculate_pca <- function(counts, center = TRUE, scale = FALSE) {
#' @noRd
calculate_pcoa <- function(counts, method = "euclidean", nmds = FALSE) {
# Remove samples with missing values
- completeCases <- complete.cases(counts)
+ completeCases <- stats::complete.cases(counts)
counts_clean <- counts[completeCases, ]
if (nrow(counts_clean) < 3 || ncol(counts_clean) < 3) {
@@ -1293,7 +1296,7 @@ calculate_pcoa <- function(counts, method = "euclidean", nmds = FALSE) {
# Classical PCoA
pcoa_result <- tryCatch(
{
- cmdscale(dist_mat, k = min(10, nrow(counts_clean) - 1), eig = TRUE)
+ stats::cmdscale(dist_mat, k = min(10, nrow(counts_clean) - 1), eig = TRUE)
},
error = function(e) {
return(NULL)
@@ -1426,7 +1429,7 @@ prepare_biplot_data <- function(
# Manual selection: use custom_genes
if (!is.null(custom_genes) && length(custom_genes) > 0) {
genes_to_plot <- loadings_subset %>%
- dplyr::filter(gene %in% custom_genes)
+ dplyr::filter(.data$gene %in% custom_genes)
} else {
genes_to_plot <- loadings_subset[0, ] # Empty tibble if no genes specified
}
@@ -1434,22 +1437,22 @@ prepare_biplot_data <- function(
# Per-PC selection: top N from each PC separately
top_x <- loadings_subset %>%
dplyr::arrange(dplyr::desc(abs(.data[[pc_x_name]]))) %>%
- head(top_n) %>%
+ utils::head(top_n) %>%
dplyr::mutate(pc_source = pc_x_name)
top_y <- loadings_subset %>%
dplyr::arrange(dplyr::desc(abs(.data[[pc_y_name]]))) %>%
- head(top_n) %>%
+ utils::head(top_n) %>%
dplyr::mutate(pc_source = pc_y_name)
# Combine and deduplicate - keep first occurrence (prioritize PC X if gene is in both)
genes_to_plot <- dplyr::bind_rows(top_x, top_y) %>%
- dplyr::distinct(gene, .keep_all = TRUE)
+ dplyr::distinct(.data$gene, .keep_all = TRUE)
} else {
# Overall selection: top N by combined magnitude (default behavior)
genes_to_plot <- loadings_subset %>%
- dplyr::arrange(dplyr::desc(magnitude)) %>%
- head(top_n)
+ dplyr::arrange(dplyr::desc(.data$magnitude)) %>%
+ utils::head(top_n)
}
list(
@@ -1498,7 +1501,11 @@ step_log2 <- function(counts, dataset, counts_type) {
step_batch_correction <- function(counts, dataset, batch_column, design_column = "None") {
if (!is.null(batch_column) && nzchar(batch_column) && batch_column != "None") {
if (any(is.na(dataset[[batch_column]]))) {
- showNotification("Batch correction skipped: batch column contains NA values", type = "warning", duration = 8)
+ shiny::showNotification(
+ "Batch correction skipped: batch column contains NA values",
+ type = "warning",
+ duration = 8
+ )
} else {
counts <- apply_batch_correction(
counts = counts,
@@ -1517,8 +1524,8 @@ step_batch_correction <- function(counts, dataset, batch_column, design_column =
step_top_n_sd <- function(counts, dataset, top_n) {
top_n <- min(top_n, nrow(counts))
if (nrow(counts) > top_n) {
- sds <- apply(counts, 1, sd, na.rm = FALSE)
- top_features <- names(head(sort(sds, decreasing = TRUE), n = top_n))
+ sds <- apply(counts, 1, stats::sd, na.rm = FALSE)
+ top_features <- names(utils::head(sort(sds, decreasing = TRUE), n = top_n))
counts <- counts[top_features, , drop = FALSE]
}
list(counts = counts, dataset = dataset)
@@ -1534,36 +1541,37 @@ plot_ordination_samples <- function(ordination_result, pc_scores, input, colours
pc_y <- input$pcaY
# Base plot
- p <- ggplot(pc_scores, aes(x = .data[[pc_x]], y = .data[[pc_y]], fill = .data[[input$pcaFactor1]]))
+ p <- ggplot2::ggplot(pc_scores, ggplot2::aes(x = .data[[pc_x]], y = .data[[pc_y]], fill = .data[[input$pcaFactor1]]))
if (input$pcaAddEllipses) {
p <- p +
- stat_ellipse(
- aes(colour = .data[[input$pcaFactor1]], fill = .data[[input$pcaFactor1]]),
+ ggplot2::stat_ellipse(
+ ggplot2::aes(colour = .data[[input$pcaFactor1]], fill = .data[[input$pcaFactor1]]),
geom = "polygon",
alpha = input$pcaEllipsesAlpha,
show.legend = FALSE
)
- p <- p + scale_colour_manual(breaks = names(coloursPCA), values = as.character(coloursPCA))
+ p <- p + ggplot2::scale_colour_manual(breaks = names(coloursPCA), values = as.character(coloursPCA))
}
if (input$pcaFactor2 == "None") {
- p <- p + geom_point(size = input$dotSizePCA, alpha = input$alphaPCA, shape = 21, stroke = input$dotBorderPCA)
+ p <- p +
+ ggplot2::geom_point(size = input$dotSizePCA, alpha = input$alphaPCA, shape = 21, stroke = input$dotBorderPCA)
} else {
p <- p +
- geom_point(
- aes(shape = .data[[input$pcaFactor2]]),
+ ggplot2::geom_point(
+ ggplot2::aes(shape = .data[[input$pcaFactor2]]),
size = input$dotSizePCA,
alpha = input$alphaPCA,
stroke = input$dotBorderPCA
)
- p <- p + scale_shape_manual(values = c(21, 22, 23, 24, 25, 8, 3, 4), labels = shapeLabels)
+ p <- p + ggplot2::scale_shape_manual(values = c(21, 22, 23, 24, 25, 8, 3, 4), labels = shapeLabels)
}
if (input$pcaShowNames) {
p <- p +
- geom_label_repel(
- aes(label = Name, fill = .data[[input$pcaFactor1]]),
+ ggrepel::geom_label_repel(
+ ggplot2::aes(label = .data$Name, fill = .data[[input$pcaFactor1]]),
force = 2,
nudge_y = as.numeric(input$geneLabelNudgePCAY) / 10,
nudge_x = as.numeric(input$geneLabelNudgePCAX) / 10,
@@ -1589,18 +1597,20 @@ plot_ordination_samples <- function(ordination_result, pc_scores, input, colours
y_lab <- pc_y
}
- p <- p + labs(x = x_lab, y = y_lab, fill = input$pcaFactor1)
+ p <- p + ggplot2::labs(x = x_lab, y = y_lab, fill = input$pcaFactor1)
if (input$pcaAxesProp && !is.null(ordination_result$variance)) {
pc_x_num <- as.numeric(gsub("\\D", "", pc_x))
pc_y_num <- as.numeric(gsub("\\D", "", pc_y))
- p <- p + coord_fixed(ratio = ordination_result$variance[pc_y_num] / ordination_result$variance[pc_x_num])
+ p <- p + ggplot2::coord_fixed(ratio = ordination_result$variance[pc_y_num] / ordination_result$variance[pc_x_num])
}
- p <- p + scale_fill_manual(breaks = names(coloursPCA), values = as.character(coloursPCA), labels = fillLabels)
- p <- p + theme_bw(base_size = input$textSizePCA)
+ p <- p +
+ ggplot2::scale_fill_manual(breaks = names(coloursPCA), values = as.character(coloursPCA), labels = fillLabels)
+ p <- p + ggplot2::theme_bw(base_size = input$textSizePCA)
face <- switch(input$boldPCA, "TRUE" = "bold", "FALSE" = "plain")
- p <- p + theme(axis.text = element_text(face = face), axis.title = element_text(face = face))
+ p <- p +
+ ggplot2::theme(axis.text = ggplot2::element_text(face = face), axis.title = ggplot2::element_text(face = face))
if (isTRUE(levelLabels$rich)) {
p <- p + rich_label_theme(legend = TRUE)
}
@@ -1608,25 +1618,25 @@ plot_ordination_samples <- function(ordination_result, pc_scores, input, colours
# Conditionally hide grid lines
if (!input$showLinesPCA) {
p <- p +
- theme(
- panel.grid.major.x = element_blank(),
- panel.grid.minor.x = element_blank(),
- panel.grid.major.y = element_blank(),
- panel.grid.minor.y = element_blank()
+ ggplot2::theme(
+ panel.grid.major.x = ggplot2::element_blank(),
+ panel.grid.minor.x = ggplot2::element_blank(),
+ panel.grid.major.y = ggplot2::element_blank(),
+ panel.grid.minor.y = ggplot2::element_blank()
)
}
# Conditionally hide axes
if (!input$showAxesPCA) {
p <- p +
- theme(
- axis.line = element_blank(),
- axis.text.x = element_blank(),
- axis.text.y = element_blank(),
- axis.ticks = element_blank(),
- axis.title.x = element_blank(),
- axis.title.y = element_blank(),
- panel.border = element_blank()
+ ggplot2::theme(
+ axis.line = ggplot2::element_blank(),
+ axis.text.x = ggplot2::element_blank(),
+ axis.text.y = ggplot2::element_blank(),
+ axis.ticks = ggplot2::element_blank(),
+ axis.title.x = ggplot2::element_blank(),
+ axis.title.y = ggplot2::element_blank(),
+ panel.border = ggplot2::element_blank()
)
}
@@ -1662,27 +1672,27 @@ plot_ordination_biplot <- function(
# Add arrow color column for per_pc mode
if (selection_method == "per_pc" && "pc_source" %in% names(biplot_data$gene_data)) {
biplot_data$gene_data <- biplot_data$gene_data %>%
- dplyr::mutate(arrow_color = ifelse(pc_source == pc_x, arrow_colour$x, arrow_colour$y))
+ dplyr::mutate(arrow_color = ifelse(.data$pc_source == pc_x, arrow_colour$x, arrow_colour$y))
} else {
# Single color for all arrows
biplot_data$gene_data$arrow_color <- if (is.list(arrow_colour)) arrow_colour$x else arrow_colour
}
- p <- ggplot()
+ p <- ggplot2::ggplot()
p <- p +
- geom_point(
+ ggplot2::geom_point(
data = pc_scores,
- aes(x = .data[[pc_x]], y = .data[[pc_y]], fill = .data[[input$pcaFactor1]]),
+ ggplot2::aes(x = .data[[pc_x]], y = .data[[pc_y]], fill = .data[[input$pcaFactor1]]),
size = input$dotSizePCA,
alpha = input$alphaPCA,
shape = 21,
stroke = input$dotBorderPCA
)
p <- p +
- geom_segment(
+ ggplot2::geom_segment(
data = biplot_data$gene_data,
- aes(x = 0, y = 0, xend = pc_x_scaled, yend = pc_y_scaled, colour = arrow_color),
- arrow = arrow(length = unit(0.2, "cm"), type = "closed"),
+ ggplot2::aes(x = 0, y = 0, xend = .data$pc_x_scaled, yend = .data$pc_y_scaled, colour = .data$arrow_color),
+ arrow = grid::arrow(length = grid::unit(0.2, "cm"), type = "closed"),
linewidth = 0.5,
alpha = 0.7
)
@@ -1691,14 +1701,14 @@ plot_ordination_biplot <- function(
biplot_data$gene_data$label <- biplot_data$gene_data$gene
}
p <- p +
- geom_text_repel(
+ ggrepel::geom_text_repel(
data = biplot_data$gene_data,
- aes(x = pc_x_scaled, y = pc_y_scaled, label = label, colour = arrow_color),
+ ggplot2::aes(x = .data$pc_x_scaled, y = .data$pc_y_scaled, label = .data$label, colour = .data$arrow_color),
size = input$textSizePCA / 4,
fontface = "bold",
max.overlaps = 20
)
- p <- p + scale_colour_identity() # Use the actual color values
+ p <- p + ggplot2::scale_colour_identity() # Use the actual color values
# Axes
if (!is.null(ordination_result$variance)) {
@@ -1711,11 +1721,13 @@ plot_ordination_biplot <- function(
y_lab <- pc_y
}
- p <- p + labs(x = x_lab, y = y_lab, fill = input$pcaFactor1)
- p <- p + scale_fill_manual(breaks = names(coloursPCA), values = as.character(coloursPCA), labels = fillLabels)
- p <- p + theme_bw(base_size = input$textSizePCA)
+ p <- p + ggplot2::labs(x = x_lab, y = y_lab, fill = input$pcaFactor1)
+ p <- p +
+ ggplot2::scale_fill_manual(breaks = names(coloursPCA), values = as.character(coloursPCA), labels = fillLabels)
+ p <- p + ggplot2::theme_bw(base_size = input$textSizePCA)
face <- switch(input$boldPCA, "TRUE" = "bold", "FALSE" = "plain")
- p <- p + theme(axis.text = element_text(face = face), axis.title = element_text(face = face))
+ p <- p +
+ ggplot2::theme(axis.text = ggplot2::element_text(face = face), axis.title = ggplot2::element_text(face = face))
if (isTRUE(levelLabels$rich)) {
p <- p + rich_label_theme(legend = TRUE)
}
@@ -1723,25 +1735,25 @@ plot_ordination_biplot <- function(
# Conditionally hide grid lines
if (!input$showLinesPCA) {
p <- p +
- theme(
- panel.grid.major.x = element_blank(),
- panel.grid.minor.x = element_blank(),
- panel.grid.major.y = element_blank(),
- panel.grid.minor.y = element_blank()
+ ggplot2::theme(
+ panel.grid.major.x = ggplot2::element_blank(),
+ panel.grid.minor.x = ggplot2::element_blank(),
+ panel.grid.major.y = ggplot2::element_blank(),
+ panel.grid.minor.y = ggplot2::element_blank()
)
}
# Conditionally hide axes
if (!input$showAxesPCA) {
p <- p +
- theme(
- axis.line = element_blank(),
- axis.text.x = element_blank(),
- axis.text.y = element_blank(),
- axis.ticks = element_blank(),
- axis.title.x = element_blank(),
- axis.title.y = element_blank(),
- panel.border = element_blank()
+ ggplot2::theme(
+ axis.line = ggplot2::element_blank(),
+ axis.text.x = ggplot2::element_blank(),
+ axis.text.y = ggplot2::element_blank(),
+ axis.ticks = ggplot2::element_blank(),
+ axis.title.x = ggplot2::element_blank(),
+ axis.title.y = ggplot2::element_blank(),
+ panel.border = ggplot2::element_blank()
)
}
@@ -1804,7 +1816,7 @@ make_qc_scatter <- function(
df$types <- factor(df$types, levels = draw_order)
df <- df[order(df$types), , drop = FALSE]
- p <- ggplot2::ggplot(df, ggplot2::aes(x = x, y = y, colour = types)) +
+ p <- ggplot2::ggplot(df, ggplot2::aes(x = x, y = y, colour = .data$types)) +
ggplot2::geom_point(size = point_size, alpha = alpha) +
ggplot2::scale_color_manual(values = types_colours)
if (isTRUE(log_scale)) {
diff --git a/R/legacy_glue.R b/R/legacy_glue.R
index 91e9338..6029a5f 100644
--- a/R/legacy_glue.R
+++ b/R/legacy_glue.R
@@ -69,7 +69,7 @@ legacy_gStoreList_from_eds <- function(eds, se = NULL, dataDir = NULL, param = N
factors_raw <- colnames(colData_raw)[grep("\\[Factor]", colnames(colData_raw))]
factors <- gsub(" \\[.*", "", factors_raw)
factors <- gsub(" ", "_", factors)
- factorLevels <- setNames(
+ factorLevels <- stats::setNames(
lapply(factors, function(f) levels(as.factor(dataset[[f]]))),
factors
)
@@ -112,9 +112,7 @@ legacy_gStoreList_from_eds <- function(eds, se = NULL, dataDir = NULL, param = N
if (isTRUE(param$featureLevel == "isoform")) {
idOrder <- intersect(rd$transcript_id, rownames(countList[[i]]))
countList[[i]] <- countList[[i]][idOrder, ]
- rownames(countList[[i]]) <- rd$feature_id %>%
- gsub("[:/()-]", ".", .) %>%
- gsub(" ", ".", .)
+ rownames(countList[[i]]) <- gsub(" ", ".", gsub("[:/()-]", ".", rd$feature_id))
} else {
idOrder <- intersect(rd$gene_id, rownames(countList[[i]]))
countList[[i]] <- countList[[i]][idOrder, ]
@@ -167,7 +165,7 @@ legacy_gStoreList_from_eds <- function(eds, se = NULL, dataDir = NULL, param = N
gStoreList$design <- dataTypeGStore
gStoreList$designLevels <- NULL
if (dataTypeGStore == "CrisprCountQC") {
- gStoreList$sgRNA_to_gene <- setNames(
+ gStoreList$sgRNA_to_gene <- stats::setNames(
gsub("_((sgrna)?[0-9]+|[+-]_[^_]+)_[ACGTN]+$", "", rd$feature_id, ignore.case = TRUE),
rd$feature_id
)
@@ -383,7 +381,7 @@ legacy_multi_contrast_from_eds <- function(eds, contrast) {
}
factors <- eds$factor_names()
- factorLevels <- setNames(lapply(factors, function(f) eds$factor_levels(f)), factors)
+ factorLevels <- stats::setNames(lapply(factors, function(f) eds$factor_levels(f)), factors)
# ---- seqAnno = feature annotation + this contrast's DE stats ------------
de <- eds$de(contrast) # feature_id, log2Ratio, pValue, fdr, gene_name, ...
@@ -469,14 +467,14 @@ legacy_multi_contrast_from_eds <- function(eds, contrast) {
]
contrasts <- gsub("constrast_", "", contrasts)
- contrast_dfs <- setNames(
+ contrast_dfs <- stats::setNames(
lapply(contrasts, function(con) {
as.data.frame(SummarizedExperiment::rowData(se)[[paste0("constrast_", con)]])
}),
contrasts
)
- seqAnnoList <- setNames(
+ seqAnnoList <- stats::setNames(
lapply(contrasts, function(con) {
# .saint_standardise_de maps SAINT's log2_EFCs/BFDR -> log2Ratio/fdr and
# adds an all-NA pValue (no-op for standard prolfqua frames); .de_order_idx
@@ -510,7 +508,7 @@ legacy_multi_contrast_from_eds <- function(eds, contrast) {
factors <- colnames(dataset)[
grep("Sample|Name|names|channel|raw\\.file", colnames(dataset), invert = TRUE, ignore.case = TRUE)
]
- factorLevels <- setNames(
+ factorLevels <- stats::setNames(
lapply(factors, function(f) levels(as.factor(dataset[[f]]))),
factors
)
@@ -522,9 +520,9 @@ legacy_multi_contrast_from_eds <- function(eds, contrast) {
unsorted_sa <- standardise_columns(contrast_dfs[[contrasts[1]]])
unsorted_sa$feature_id <- build_feature_id(unsorted_sa)
raw_rn <- rownames(contrast_dfs[[contrasts[1]]])
- fid_lookup <- setNames(unsorted_sa$feature_id, raw_rn)
+ fid_lookup <- stats::setNames(unsorted_sa$feature_id, raw_rn)
- countList <- setNames(
+ countList <- stats::setNames(
lapply(names(SummarizedExperiment::assays(se)), function(ass) {
x <- SummarizedExperiment::assay(se, ass)
mapped <- fid_lookup[rownames(x)]
diff --git a/R/utils_explore_dataset.R b/R/utils_explore_dataset.R
index bf86ba4..d303ee8 100644
--- a/R/utils_explore_dataset.R
+++ b/R/utils_explore_dataset.R
@@ -204,7 +204,7 @@ eds_infer_organism <- function(param) {
eds_flatten_cp_results <- function(x, prefix = "") {
if (inherits(x, c("enrichResult", "gseaResult")) || is.data.frame(x)) {
nm <- if (nzchar(prefix)) prefix else "default"
- return(setNames(list(x), nm))
+ return(stats::setNames(list(x), nm))
}
if (is.list(x) && length(x)) {
out <- list()
@@ -423,7 +423,7 @@ eds_load_se <- function(input) {
lists <- Filter(function(gl) length(gl) > 0L, lists)
if (length(lists)) {
shared <- all(vapply(lists, identical, logical(1), lists[[1]]))
- use <- if (shared) setNames(lists[1], "*") else lists
+ use <- if (shared) stats::setNames(lists[1], "*") else lists
out$gene_list <- do.call(
rbind,
lapply(names(use), function(ont) {
@@ -449,7 +449,7 @@ eds_load_se <- function(input) {
}
gsea <- identical(support$class, "gseaResult")
onts <- unique(tidy$ontology)
- setNames(
+ stats::setNames(
lapply(onts, function(ont) {
r <- tidy[tidy$ontology == ont, setdiff(colnames(tidy), c("method", "ontology")), drop = FALSE]
r <- r[, vapply(r, function(col) !all(is.na(col)), logical(1)), drop = FALSE] # rbind.fill padding
diff --git a/man/ExploreDataset.Rd b/man/ExploreDataset.Rd
index 303aab2..adffbad 100644
--- a/man/ExploreDataset.Rd
+++ b/man/ExploreDataset.Rd
@@ -8,8 +8,7 @@
subclass must implement. It is not instantiable on its own — calling
`ExploreDataset$new()` raises an error. Use [new_explore_dataset()] to
build a concrete instance, or instantiate a subclass directly.
-}
-\details{
+
Methods implemented on the base class read only from
`private$.config` and are inherited unchanged by every subclass.
Methods that touch the storage backend are virtual
@@ -17,515 +16,800 @@ Methods that touch the storage backend are virtual
}
\section{Methods}{
\subsection{Public methods}{
-\itemize{
-\item \href{#method-ExploreDataset-new}{\code{ExploreDataset$new()}}
-\item \href{#method-ExploreDataset-omics_class}{\code{ExploreDataset$omics_class()}}
-\item \href{#method-ExploreDataset-data_type}{\code{ExploreDataset$data_type()}}
-\item \href{#method-ExploreDataset-has_de}{\code{ExploreDataset$has_de()}}
-\item \href{#method-ExploreDataset-has_enrichment}{\code{ExploreDataset$has_enrichment()}}
-\item \href{#method-ExploreDataset-organism}{\code{ExploreDataset$organism()}}
-\item \href{#method-ExploreDataset-ref_build}{\code{ExploreDataset$ref_build()}}
-\item \href{#method-ExploreDataset-feature_id_kind}{\code{ExploreDataset$feature_id_kind()}}
-\item \href{#method-ExploreDataset-background_expression}{\code{ExploreDataset$background_expression()}}
-\item \href{#method-ExploreDataset-backend_kind}{\code{ExploreDataset$backend_kind()}}
-\item \href{#method-ExploreDataset-backend}{\code{ExploreDataset$backend()}}
-\item \href{#method-ExploreDataset-samples}{\code{ExploreDataset$samples()}}
-\item \href{#method-ExploreDataset-sample_ids}{\code{ExploreDataset$sample_ids()}}
-\item \href{#method-ExploreDataset-n_samples}{\code{ExploreDataset$n_samples()}}
-\item \href{#method-ExploreDataset-factor_names}{\code{ExploreDataset$factor_names()}}
-\item \href{#method-ExploreDataset-factor_levels}{\code{ExploreDataset$factor_levels()}}
-\item \href{#method-ExploreDataset-primary_grouping}{\code{ExploreDataset$primary_grouping()}}
-\item \href{#method-ExploreDataset-secondary_grouping}{\code{ExploreDataset$secondary_grouping()}}
-\item \href{#method-ExploreDataset-sample_factor}{\code{ExploreDataset$sample_factor()}}
-\item \href{#method-ExploreDataset-features}{\code{ExploreDataset$features()}}
-\item \href{#method-ExploreDataset-feature_ids}{\code{ExploreDataset$feature_ids()}}
-\item \href{#method-ExploreDataset-n_features}{\code{ExploreDataset$n_features()}}
-\item \href{#method-ExploreDataset-feature_display}{\code{ExploreDataset$feature_display()}}
-\item \href{#method-ExploreDataset-assay_names}{\code{ExploreDataset$assay_names()}}
-\item \href{#method-ExploreDataset-has_assay}{\code{ExploreDataset$has_assay()}}
-\item \href{#method-ExploreDataset-assay}{\code{ExploreDataset$assay()}}
-\item \href{#method-ExploreDataset-assay_label}{\code{ExploreDataset$assay_label()}}
-\item \href{#method-ExploreDataset-raw_assay_name}{\code{ExploreDataset$raw_assay_name()}}
-\item \href{#method-ExploreDataset-primary_assay_name}{\code{ExploreDataset$primary_assay_name()}}
-\item \href{#method-ExploreDataset-raw_assay}{\code{ExploreDataset$raw_assay()}}
-\item \href{#method-ExploreDataset-primary_assay}{\code{ExploreDataset$primary_assay()}}
-\item \href{#method-ExploreDataset-contrasts}{\code{ExploreDataset$contrasts()}}
-\item \href{#method-ExploreDataset-primary_contrast}{\code{ExploreDataset$primary_contrast()}}
-\item \href{#method-ExploreDataset-de}{\code{ExploreDataset$de()}}
-\item \href{#method-ExploreDataset-de_all}{\code{ExploreDataset$de_all()}}
-\item \href{#method-ExploreDataset-contrast_meta}{\code{ExploreDataset$contrast_meta()}}
-\item \href{#method-ExploreDataset-contrast_label}{\code{ExploreDataset$contrast_label()}}
-\item \href{#method-ExploreDataset-de_display_extras}{\code{ExploreDataset$de_display_extras()}}
-\item \href{#method-ExploreDataset-has_pvalue}{\code{ExploreDataset$has_pvalue()}}
-\item \href{#method-ExploreDataset-enrichment_kinds}{\code{ExploreDataset$enrichment_kinds()}}
-\item \href{#method-ExploreDataset-enrichment}{\code{ExploreDataset$enrichment()}}
-\item \href{#method-ExploreDataset-enrichment_input}{\code{ExploreDataset$enrichment_input()}}
-\item \href{#method-ExploreDataset-enrichment_table}{\code{ExploreDataset$enrichment_table()}}
-\item \href{#method-ExploreDataset-enrichment_filter}{\code{ExploreDataset$enrichment_filter()}}
-\item \href{#method-ExploreDataset-sgrna_to_gene}{\code{ExploreDataset$sgrna_to_gene()}}
-\item \href{#method-ExploreDataset-proteomics_choices}{\code{ExploreDataset$proteomics_choices()}}
-\item \href{#method-ExploreDataset-all_pathways}{\code{ExploreDataset$all_pathways()}}
-\item \href{#method-ExploreDataset-source}{\code{ExploreDataset$source()}}
-\item \href{#method-ExploreDataset-print}{\code{ExploreDataset$print()}}
-\item \href{#method-ExploreDataset-clone}{\code{ExploreDataset$clone()}}
-}
-}
-\if{html}{\out{
}}
-\if{html}{\out{}}
-\if{latex}{\out{\hypertarget{method-ExploreDataset-new}{}}}
-\subsection{Method \code{new()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$new(...)}\if{html}{\out{
}}
+ \itemize{
+ \item \href{#method-ExploreDataset-initialize}{\code{ExploreDataset$new()}}
+ \item \href{#method-ExploreDataset-omics_class}{\code{ExploreDataset$omics_class()}}
+ \item \href{#method-ExploreDataset-data_type}{\code{ExploreDataset$data_type()}}
+ \item \href{#method-ExploreDataset-has_de}{\code{ExploreDataset$has_de()}}
+ \item \href{#method-ExploreDataset-has_enrichment}{\code{ExploreDataset$has_enrichment()}}
+ \item \href{#method-ExploreDataset-organism}{\code{ExploreDataset$organism()}}
+ \item \href{#method-ExploreDataset-ref_build}{\code{ExploreDataset$ref_build()}}
+ \item \href{#method-ExploreDataset-feature_id_kind}{\code{ExploreDataset$feature_id_kind()}}
+ \item \href{#method-ExploreDataset-background_expression}{\code{ExploreDataset$background_expression()}}
+ \item \href{#method-ExploreDataset-backend_kind}{\code{ExploreDataset$backend_kind()}}
+ \item \href{#method-ExploreDataset-backend}{\code{ExploreDataset$backend()}}
+ \item \href{#method-ExploreDataset-samples}{\code{ExploreDataset$samples()}}
+ \item \href{#method-ExploreDataset-sample_ids}{\code{ExploreDataset$sample_ids()}}
+ \item \href{#method-ExploreDataset-n_samples}{\code{ExploreDataset$n_samples()}}
+ \item \href{#method-ExploreDataset-factor_names}{\code{ExploreDataset$factor_names()}}
+ \item \href{#method-ExploreDataset-factor_levels}{\code{ExploreDataset$factor_levels()}}
+ \item \href{#method-ExploreDataset-primary_grouping}{\code{ExploreDataset$primary_grouping()}}
+ \item \href{#method-ExploreDataset-secondary_grouping}{\code{ExploreDataset$secondary_grouping()}}
+ \item \href{#method-ExploreDataset-sample_factor}{\code{ExploreDataset$sample_factor()}}
+ \item \href{#method-ExploreDataset-features}{\code{ExploreDataset$features()}}
+ \item \href{#method-ExploreDataset-feature_ids}{\code{ExploreDataset$feature_ids()}}
+ \item \href{#method-ExploreDataset-n_features}{\code{ExploreDataset$n_features()}}
+ \item \href{#method-ExploreDataset-feature_display}{\code{ExploreDataset$feature_display()}}
+ \item \href{#method-ExploreDataset-assay_names}{\code{ExploreDataset$assay_names()}}
+ \item \href{#method-ExploreDataset-has_assay}{\code{ExploreDataset$has_assay()}}
+ \item \href{#method-ExploreDataset-assay}{\code{ExploreDataset$assay()}}
+ \item \href{#method-ExploreDataset-assay_label}{\code{ExploreDataset$assay_label()}}
+ \item \href{#method-ExploreDataset-raw_assay_name}{\code{ExploreDataset$raw_assay_name()}}
+ \item \href{#method-ExploreDataset-primary_assay_name}{\code{ExploreDataset$primary_assay_name()}}
+ \item \href{#method-ExploreDataset-raw_assay}{\code{ExploreDataset$raw_assay()}}
+ \item \href{#method-ExploreDataset-primary_assay}{\code{ExploreDataset$primary_assay()}}
+ \item \href{#method-ExploreDataset-contrasts}{\code{ExploreDataset$contrasts()}}
+ \item \href{#method-ExploreDataset-primary_contrast}{\code{ExploreDataset$primary_contrast()}}
+ \item \href{#method-ExploreDataset-de}{\code{ExploreDataset$de()}}
+ \item \href{#method-ExploreDataset-de_all}{\code{ExploreDataset$de_all()}}
+ \item \href{#method-ExploreDataset-contrast_meta}{\code{ExploreDataset$contrast_meta()}}
+ \item \href{#method-ExploreDataset-contrast_label}{\code{ExploreDataset$contrast_label()}}
+ \item \href{#method-ExploreDataset-de_display_extras}{\code{ExploreDataset$de_display_extras()}}
+ \item \href{#method-ExploreDataset-has_pvalue}{\code{ExploreDataset$has_pvalue()}}
+ \item \href{#method-ExploreDataset-enrichment_kinds}{\code{ExploreDataset$enrichment_kinds()}}
+ \item \href{#method-ExploreDataset-enrichment}{\code{ExploreDataset$enrichment()}}
+ \item \href{#method-ExploreDataset-enrichment_input}{\code{ExploreDataset$enrichment_input()}}
+ \item \href{#method-ExploreDataset-enrichment_table}{\code{ExploreDataset$enrichment_table()}}
+ \item \href{#method-ExploreDataset-enrichment_filter}{\code{ExploreDataset$enrichment_filter()}}
+ \item \href{#method-ExploreDataset-sgrna_to_gene}{\code{ExploreDataset$sgrna_to_gene()}}
+ \item \href{#method-ExploreDataset-proteomics_choices}{\code{ExploreDataset$proteomics_choices()}}
+ \item \href{#method-ExploreDataset-all_pathways}{\code{ExploreDataset$all_pathways()}}
+ \item \href{#method-ExploreDataset-source}{\code{ExploreDataset$source()}}
+ \item \href{#method-ExploreDataset-print}{\code{ExploreDataset$print()}}
+ \item \href{#method-ExploreDataset-clone}{\code{ExploreDataset$clone()}}
+ }
+}
+\if{html}{\out{
}}
+\if{html}{\out{}}
+\if{latex}{\out{\hypertarget{method-ExploreDataset-initialize}{}}}
+\subsection{\code{ExploreDataset$new()}}{
+ Always errors: the base class is abstract. Use [new_explore_dataset()] or a concrete subclass.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$new(...)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{...}}{Ignored.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-omics_class}{}}}
-\subsection{Method \code{omics_class()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$omics_class()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$omics_class()}}{
+ Omics class from the config: `"genomics"` or `"proteomics"`.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$omics_class()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-data_type}{}}}
-\subsection{Method \code{data_type()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$data_type()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$data_type()}}{
+ Dataset type from the config, e.g. `"RNASeq"`, `"CountQC"`, `"CrisprCountQC"` or `"proteomics"`.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$data_type()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-has_de}{}}}
-\subsection{Method \code{has_de()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$has_de()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$has_de()}}{
+ `TRUE` when the dataset has at least one contrast.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$has_de()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-has_enrichment}{}}}
-\subsection{Method \code{has_enrichment()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$has_enrichment()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$has_enrichment()}}{
+ `TRUE` when the config lists at least one enrichment kind.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$has_enrichment()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-organism}{}}}
-\subsection{Method \code{organism()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$organism()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$organism()}}{
+ Organism from the config, or `NA` when unknown.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$organism()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-ref_build}{}}}
-\subsection{Method \code{ref_build()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$ref_build()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$ref_build()}}{
+ Reference genome build from the config, or `NA` when unknown.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$ref_build()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-feature_id_kind}{}}}
-\subsection{Method \code{feature_id_kind()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$feature_id_kind()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$feature_id_kind()}}{
+ What a feature ID denotes, from the config, e.g. `"gene"`, `"isoform"`, `"protein"`,
+ `"peptide"`, `"phospho"` or `"guide"`.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$feature_id_kind()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-background_expression}{}}}
-\subsection{Method \code{background_expression()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$background_expression()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$background_expression()}}{
+ Low-signal offset added to expression values before taking log2; from the config, default 10.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$background_expression()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-backend_kind}{}}}
-\subsection{Method \code{backend_kind()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$backend_kind()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$backend_kind()}}{
+ Short tag naming the storage backend (`"se"`, `"h5ad"` or `"parquet"`). Implemented by subclasses.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$backend_kind()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-backend}{}}}
-\subsection{Method \code{backend()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$backend()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$backend()}}{
+ The underlying storage object. Implemented by subclasses.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$backend()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-samples}{}}}
-\subsection{Method \code{samples()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$samples()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$samples()}}{
+ Sample metadata as a data.frame, one row per sample, rownames are sample IDs.
+ Implemented by subclasses.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$samples()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-sample_ids}{}}}
-\subsection{Method \code{sample_ids()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$sample_ids()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$sample_ids()}}{
+ Sample IDs: the rownames of `samples()`.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$sample_ids()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-n_samples}{}}}
-\subsection{Method \code{n_samples()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$n_samples()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$n_samples()}}{
+ Number of samples: the number of rows of `samples()`.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$n_samples()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-factor_names}{}}}
-\subsection{Method \code{factor_names()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$factor_names()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$factor_names()}}{
+ Names of the experimental factors from the config; empty when there are none.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$factor_names()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-factor_levels}{}}}
-\subsection{Method \code{factor_levels()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$factor_levels(factor)}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$factor_levels()}}{
+ Levels of one experimental factor, from the config.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$factor_levels(factor)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{factor}}{Factor name, one of `factor_names()`.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-primary_grouping}{}}}
-\subsection{Method \code{primary_grouping()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$primary_grouping()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$primary_grouping()}}{
+ Name of the factor used as the primary sample grouping, from the config.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$primary_grouping()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-secondary_grouping}{}}}
-\subsection{Method \code{secondary_grouping()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$secondary_grouping()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$secondary_grouping()}}{
+ Name of the secondary grouping factor, or `NA` when there is none.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$secondary_grouping()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-sample_factor}{}}}
-\subsection{Method \code{sample_factor()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$sample_factor(factor)}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$sample_factor()}}{
+ One column of `samples()`: the values of a factor, one per sample.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$sample_factor(factor)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{factor}}{Column name in `samples()`, usually one of `factor_names()`.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-features}{}}}
-\subsection{Method \code{features()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$features()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$features()}}{
+ Feature annotation as a data.frame, one row per feature, rownames are feature IDs, with a
+ `display_name` column. Implemented by subclasses.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$features()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-feature_ids}{}}}
-\subsection{Method \code{feature_ids()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$feature_ids()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$feature_ids()}}{
+ Feature IDs: the rownames of `features()`.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$feature_ids()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-n_features}{}}}
-\subsection{Method \code{n_features()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$n_features()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$n_features()}}{
+ Number of features: the number of rows of `features()`.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$n_features()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-feature_display}{}}}
-\subsection{Method \code{feature_display()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$feature_display(ids = NULL)}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$feature_display()}}{
+ Display names of features, named by feature ID.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$feature_display(ids = NULL)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{ids}}{Feature IDs to look up; `NULL` (default) returns all features.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-assay_names}{}}}
-\subsection{Method \code{assay_names()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$assay_names()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$assay_names()}}{
+ Canonical names of the assays this dataset provides. Implemented by subclasses.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$assay_names()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-has_assay}{}}}
-\subsection{Method \code{has_assay()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$has_assay(name)}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$has_assay()}}{
+ `TRUE` when `name` is one of `assay_names()`.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$has_assay(name)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{name}}{Canonical assay name.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-assay}{}}}
-\subsection{Method \code{assay()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$assay(name, features = NULL, samples = NULL)}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$assay()}}{
+ One assay as a features x samples matrix, optionally subset. Implemented by subclasses.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$assay(name, features = NULL, samples = NULL)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{name}}{Canonical assay name, one of `assay_names()`.}
+ \item{\code{features}}{Feature IDs (rows) to keep; `NULL` keeps all.}
+ \item{\code{samples}}{Sample IDs (columns) to keep; `NULL` keeps all.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-assay_label}{}}}
-\subsection{Method \code{assay_label()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$assay_label(name)}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$assay_label()}}{
+ Human-readable label for an assay, from the config; `name` itself when no label is registered.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$assay_label(name)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{name}}{Canonical assay name.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-raw_assay_name}{}}}
-\subsection{Method \code{raw_assay_name()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$raw_assay_name()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$raw_assay_name()}}{
+ Canonical name of the raw assay, from the config.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$raw_assay_name()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-primary_assay_name}{}}}
-\subsection{Method \code{primary_assay_name()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$primary_assay_name()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$primary_assay_name()}}{
+ Canonical name of the primary assay, from the config.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$primary_assay_name()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-raw_assay}{}}}
-\subsection{Method \code{raw_assay()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$raw_assay(...)}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$raw_assay()}}{
+ The raw assay: shortcut for `assay(raw_assay_name(), ...)`.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$raw_assay(...)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{...}}{Passed to `assay()`: `features`, `samples`.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-primary_assay}{}}}
-\subsection{Method \code{primary_assay()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$primary_assay(...)}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$primary_assay()}}{
+ The primary assay: shortcut for `assay(primary_assay_name(), ...)`.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$primary_assay(...)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{...}}{Passed to `assay()`: `features`, `samples`.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-contrasts}{}}}
-\subsection{Method \code{contrasts()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$contrasts()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$contrasts()}}{
+ Names of the DE contrasts, from the config; empty when the dataset has no DE results.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$contrasts()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-primary_contrast}{}}}
-\subsection{Method \code{primary_contrast()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$primary_contrast()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$primary_contrast()}}{
+ Name of the primary contrast, from the config; `NA` when there are no contrasts.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$primary_contrast()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-de}{}}}
-\subsection{Method \code{de()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$de(contrast)}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$de()}}{
+ DE result table for one contrast, as a data.frame. Implemented by subclasses.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$de(contrast)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{contrast}}{Contrast name, one of `contrasts()`.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-de_all}{}}}
-\subsection{Method \code{de_all()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$de_all()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$de_all()}}{
+ DE result tables of all contrasts, as a list named by contrast.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$de_all()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-contrast_meta}{}}}
-\subsection{Method \code{contrast_meta()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$contrast_meta(contrast)}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$contrast_meta()}}{
+ Metadata list of one contrast from the config: test and reference group, factor, method,
+ thresholds. Errors on an unknown contrast.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$contrast_meta(contrast)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{contrast}}{Contrast name, one of `contrasts()`.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-contrast_label}{}}}
-\subsection{Method \code{contrast_label()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$contrast_label(contrast)}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$contrast_label()}}{
+ Display label of a contrast: currently the contrast name itself. Errors on an unknown contrast.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$contrast_label(contrast)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{contrast}}{Contrast name, one of `contrasts()`.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-de_display_extras}{}}}
-\subsection{Method \code{de_display_extras()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$de_display_extras()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$de_display_extras()}}{
+ Names of extra DE columns shown for display only (e.g. `SaintScore`), from the config;
+ empty by default.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$de_display_extras()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-has_pvalue}{}}}
-\subsection{Method \code{has_pvalue()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$has_pvalue()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$has_pvalue()}}{
+ `TRUE` when the DE table of at least one contrast has a non-missing raw `pValue`;
+ `FALSE` for FDR-only producers such as SAINTexpress.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$has_pvalue()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-enrichment_kinds}{}}}
-\subsection{Method \code{enrichment_kinds()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$enrichment_kinds()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$enrichment_kinds()}}{
+ Enrichment kinds available, from the config: any of `"ora"` and `"gsea"`.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$enrichment_kinds()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-enrichment}{}}}
-\subsection{Method \code{enrichment()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$enrichment(contrast, kind)}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$enrichment()}}{
+ Enrichment results of one contrast and kind, as a flat named list of clusterProfiler results.
+ Implemented by subclasses.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$enrichment(contrast, kind)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{contrast}}{Contrast name, one of `contrasts()`.}
+ \item{\code{kind}}{`"ora"` or `"gsea"`.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-enrichment_input}{}}}
-\subsection{Method \code{enrichment_input()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$enrichment_input(contrast)}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$enrichment_input()}}{
+ Inputs for enrichment of one contrast: `list(seq_anno, ranked_l2fc, selections)`.
+ Implemented by subclasses.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$enrichment_input(contrast)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{contrast}}{Contrast name, one of `contrasts()`.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-enrichment_table}{}}}
-\subsection{Method \code{enrichment_table()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$enrichment_table(contrast, kind)}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$enrichment_table()}}{
+ Enrichment results of one contrast and kind as one tidy data.frame, derived from
+ `enrichment()`; an empty data.frame when there are none.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$enrichment_table(contrast, kind)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{contrast}}{Contrast name, one of `contrasts()`.}
+ \item{\code{kind}}{`"ora"` or `"gsea"`.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-enrichment_filter}{}}}
-\subsection{Method \code{enrichment_filter()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$enrichment_filter()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$enrichment_filter()}}{
+ The `p.adjust` cut-off applied to the stored enrichment tables, from the config;
+ `NA` when none was applied.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$enrichment_filter()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-sgrna_to_gene}{}}}
-\subsection{Method \code{sgrna_to_gene()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$sgrna_to_gene()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$sgrna_to_gene()}}{
+ Named character vector mapping sgRNA IDs to gene names (CRISPR datasets); `NULL` otherwise.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$sgrna_to_gene()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-proteomics_choices}{}}}
-\subsection{Method \code{proteomics_choices()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$proteomics_choices(kind = c("gene", "protein"))}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$proteomics_choices()}}{
+ Choices and lookup for the proteomics feature picker, `list(choices, lookup)`; `NULL` when the
+ dataset has none.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$proteomics_choices(kind = c("gene", "protein"))}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{kind}}{`"gene"` (default) or `"protein"`.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-all_pathways}{}}}
-\subsection{Method \code{all_pathways()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$all_pathways()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$all_pathways()}}{
+ GO terms named in the `GO BP`, `GO MF` and `GO CC` columns of `features()`, as
+ `"GO:ID term name"` strings; empty when those columns are absent.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$all_pathways()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-source}{}}}
-\subsection{Method \code{source()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$source()}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$source()}}{
+ Provenance list from the config: backend kind, schema version and build time.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$source()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-print}{}}}
-\subsection{Method \code{print()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$print(...)}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$print()}}{
+ Print a summary of the dataset (type, dimensions, factors, contrasts, assays, enrichment)
+ and return the object invisibly.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$print(...)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{...}}{Ignored.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDataset-clone}{}}}
-\subsection{Method \code{clone()}}{
-The objects of this class are cloneable with this method.
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDataset$clone(deep = FALSE)}\if{html}{\out{
}}
+\subsection{\code{ExploreDataset$clone()}}{
+ The objects of this class are cloneable with this method.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDataset$clone(deep = FALSE)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{deep}}{Whether to make a deep clone.}
+ }
+ \if{html}{\out{
}}
+ }
}
-\subsection{Arguments}{
-\if{html}{\out{}}
-\describe{
-\item{\code{deep}}{Whether to make a deep clone.}
-}
-\if{html}{\out{
}}
-}
-}
}
diff --git a/man/ExploreDatasetH5AD.Rd b/man/ExploreDatasetH5AD.Rd
index 1ac38e1..5790025 100644
--- a/man/ExploreDatasetH5AD.Rd
+++ b/man/ExploreDatasetH5AD.Rd
@@ -11,183 +11,273 @@ data ("bring your own data") and the eventual single backend once
producers emit canonical `.h5ad` directly.
}
\section{Super class}{
-\code{\link[exploreDE:ExploreDataset]{exploreDE::ExploreDataset}} -> \code{ExploreDatasetH5AD}
+\code{\link[exploreDE:ExploreDataset]{ExploreDataset}} -> \code{ExploreDatasetH5AD}
}
\section{Methods}{
\subsection{Public methods}{
-\itemize{
-\item \href{#method-ExploreDatasetH5AD-new}{\code{ExploreDatasetH5AD$new()}}
-\item \href{#method-ExploreDatasetH5AD-backend}{\code{ExploreDatasetH5AD$backend()}}
-\item \href{#method-ExploreDatasetH5AD-backend_kind}{\code{ExploreDatasetH5AD$backend_kind()}}
-\item \href{#method-ExploreDatasetH5AD-samples}{\code{ExploreDatasetH5AD$samples()}}
-\item \href{#method-ExploreDatasetH5AD-features}{\code{ExploreDatasetH5AD$features()}}
-\item \href{#method-ExploreDatasetH5AD-de}{\code{ExploreDatasetH5AD$de()}}
-\item \href{#method-ExploreDatasetH5AD-assay_names}{\code{ExploreDatasetH5AD$assay_names()}}
-\item \href{#method-ExploreDatasetH5AD-assay}{\code{ExploreDatasetH5AD$assay()}}
-\item \href{#method-ExploreDatasetH5AD-enrichment}{\code{ExploreDatasetH5AD$enrichment()}}
-\item \href{#method-ExploreDatasetH5AD-enrichment_table}{\code{ExploreDatasetH5AD$enrichment_table()}}
-\item \href{#method-ExploreDatasetH5AD-enrichment_input}{\code{ExploreDatasetH5AD$enrichment_input()}}
-\item \href{#method-ExploreDatasetH5AD-clone}{\code{ExploreDatasetH5AD$clone()}}
-}
-}
-\if{html}{\out{
-Inherited methods
+ \itemize{
+ \item \href{#method-ExploreDatasetH5AD-initialize}{\code{ExploreDatasetH5AD$new()}}
+ \item \href{#method-ExploreDatasetH5AD-backend}{\code{ExploreDatasetH5AD$backend()}}
+ \item \href{#method-ExploreDatasetH5AD-backend_kind}{\code{ExploreDatasetH5AD$backend_kind()}}
+ \item \href{#method-ExploreDatasetH5AD-samples}{\code{ExploreDatasetH5AD$samples()}}
+ \item \href{#method-ExploreDatasetH5AD-features}{\code{ExploreDatasetH5AD$features()}}
+ \item \href{#method-ExploreDatasetH5AD-de}{\code{ExploreDatasetH5AD$de()}}
+ \item \href{#method-ExploreDatasetH5AD-assay_names}{\code{ExploreDatasetH5AD$assay_names()}}
+ \item \href{#method-ExploreDatasetH5AD-assay}{\code{ExploreDatasetH5AD$assay()}}
+ \item \href{#method-ExploreDatasetH5AD-enrichment}{\code{ExploreDatasetH5AD$enrichment()}}
+ \item \href{#method-ExploreDatasetH5AD-enrichment_table}{\code{ExploreDatasetH5AD$enrichment_table()}}
+ \item \href{#method-ExploreDatasetH5AD-enrichment_input}{\code{ExploreDatasetH5AD$enrichment_input()}}
+ \item \href{#method-ExploreDatasetH5AD-clone}{\code{ExploreDatasetH5AD$clone()}}
+ }
+}
+\if{html}{\out{Inherited methods
-
}}
-\if{html}{\out{}}
-\if{latex}{\out{\hypertarget{method-ExploreDatasetH5AD-new}{}}}
-\subsection{Method \code{new()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetH5AD$new(input, config = NULL)}\if{html}{\out{
}}
+\if{html}{\out{}}
+\if{latex}{\out{\hypertarget{method-ExploreDatasetH5AD-initialize}{}}}
+\subsection{\code{ExploreDatasetH5AD$new()}}{
+ Read a canonical `.h5ad` or take a live AnnData, build the config from it unless one is given,
+ and prepare the feature and DE tables.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetH5AD$new(input, config = NULL)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{input}}{An `anndataR` AnnData object, or a path to an existing `.h5ad` file.}
+ \item{\code{config}}{Optional pre-built config list; built from the AnnData when `NULL`.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetH5AD-backend}{}}}
-\subsection{Method \code{backend()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetH5AD$backend()}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetH5AD$backend()}}{
+ The AnnData parts read at construction, as `list(obs, var, layers, varm, uns)` of plain R
+ objects.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetH5AD$backend()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetH5AD-backend_kind}{}}}
-\subsection{Method \code{backend_kind()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetH5AD$backend_kind()}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetH5AD$backend_kind()}}{
+ Returns `"h5ad"`.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetH5AD$backend_kind()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetH5AD-samples}{}}}
-\subsection{Method \code{samples()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetH5AD$samples()}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetH5AD$samples()}}{
+ Sample metadata from `obs`, with the `factor_` prefix stripped from column names and a `Name`
+ column added when missing.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetH5AD$samples()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetH5AD-features}{}}}
-\subsection{Method \code{features()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetH5AD$features()}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetH5AD$features()}}{
+ Feature annotation from `var`, with `feature_id` and `display_name` columns, ordered by the
+ p-value of the primary contrast.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetH5AD$features()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetH5AD-de}{}}}
-\subsection{Method \code{de()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetH5AD$de(contrast)}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetH5AD$de()}}{
+ DE table of one contrast from `varm`, with the legacy aliases `log2Ratio`, `pValue` and `fdr`
+ added; an empty data.frame when the slot is missing. Errors on an unknown contrast.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetH5AD$de(contrast)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{contrast}}{Contrast name, one of `contrasts()`.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetH5AD-assay_names}{}}}
-\subsection{Method \code{assay_names()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetH5AD$assay_names()}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetH5AD$assay_names()}}{
+ Canonical assay names from the config's assay map whose layer exists; computed assays are
+ always included.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetH5AD$assay_names()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetH5AD-assay}{}}}
-\subsection{Method \code{assay()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetH5AD$assay(name, features = NULL, samples = NULL)}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetH5AD$assay()}}{
+ One assay as a features x samples matrix (the layer transposed); `normalised`,
+ `normalised_log2`, `vst`, `fpkm` and `tpm` are computed when the config maps them to no layer.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetH5AD$assay(name, features = NULL, samples = NULL)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{name}}{Canonical assay name, one of `assay_names()`.}
+ \item{\code{features}}{Feature IDs (rows) to keep; `NULL` keeps all.}
+ \item{\code{samples}}{Sample IDs (columns) to keep; `NULL` keeps all.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetH5AD-enrichment}{}}}
-\subsection{Method \code{enrichment()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetH5AD$enrichment(contrast, kind)}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetH5AD$enrichment()}}{
+ Enrichment results of one contrast and kind: decoded from the serialised objects in older files,
+ otherwise rebuilt from `uns$enrichment` and `uns$enrichment_support`.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetH5AD$enrichment(contrast, kind)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{contrast}}{Contrast name, one of `contrasts()`.}
+ \item{\code{kind}}{`"ora"` or `"gsea"`.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetH5AD-enrichment_table}{}}}
-\subsection{Method \code{enrichment_table()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetH5AD$enrichment_table(contrast, kind)}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetH5AD$enrichment_table()}}{
+ Tidy enrichment table of one contrast and kind: the table stored in `uns$enrichment` when
+ present, otherwise derived from `enrichment()` as in the base class.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetH5AD$enrichment_table(contrast, kind)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{contrast}}{Contrast name, one of `contrasts()`.}
+ \item{\code{kind}}{`"ora"` or `"gsea"`.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetH5AD-enrichment_input}{}}}
-\subsection{Method \code{enrichment_input()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetH5AD$enrichment_input(contrast)}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetH5AD$enrichment_input()}}{
+ Enrichment inputs rebuilt from the DE table: `features()`, log2 fold changes sorted decreasing,
+ and up/down feature selections at the contrast's FDR and log2FC thresholds.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetH5AD$enrichment_input(contrast)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{contrast}}{Contrast name, one of `contrasts()`.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetH5AD-clone}{}}}
-\subsection{Method \code{clone()}}{
-The objects of this class are cloneable with this method.
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetH5AD$clone(deep = FALSE)}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetH5AD$clone()}}{
+ The objects of this class are cloneable with this method.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetH5AD$clone(deep = FALSE)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{deep}}{Whether to make a deep clone.}
+ }
+ \if{html}{\out{
}}
+ }
}
-\subsection{Arguments}{
-\if{html}{\out{}}
-\describe{
-\item{\code{deep}}{Whether to make a deep clone.}
-}
-\if{html}{\out{
}}
-}
-}
}
diff --git a/man/ExploreDatasetParquet.Rd b/man/ExploreDatasetParquet.Rd
index 201684a..e0854b1 100644
--- a/man/ExploreDatasetParquet.Rd
+++ b/man/ExploreDatasetParquet.Rd
@@ -12,160 +12,197 @@ differs.
}
\keyword{internal}
\section{Super classes}{
-\code{\link[exploreDE:ExploreDataset]{exploreDE::ExploreDataset}} -> \code{\link[exploreDE:ExploreDatasetH5AD]{exploreDE::ExploreDatasetH5AD}} -> \code{ExploreDatasetParquet}
+\code{\link[exploreDE:ExploreDataset]{ExploreDataset}} -> \code{\link[exploreDE:ExploreDatasetH5AD]{ExploreDatasetH5AD}} -> \code{ExploreDatasetParquet}
}
\section{Methods}{
\subsection{Public methods}{
-\itemize{
-\item \href{#method-ExploreDatasetParquet-new}{\code{ExploreDatasetParquet$new()}}
-\item \href{#method-ExploreDatasetParquet-backend_kind}{\code{ExploreDatasetParquet$backend_kind()}}
-\item \href{#method-ExploreDatasetParquet-enrichment}{\code{ExploreDatasetParquet$enrichment()}}
-\item \href{#method-ExploreDatasetParquet-manifest}{\code{ExploreDatasetParquet$manifest()}}
-\item \href{#method-ExploreDatasetParquet-source_dir}{\code{ExploreDatasetParquet$source_dir()}}
-\item \href{#method-ExploreDatasetParquet-verify_source}{\code{ExploreDatasetParquet$verify_source()}}
-\item \href{#method-ExploreDatasetParquet-all_pathways}{\code{ExploreDatasetParquet$all_pathways()}}
-\item \href{#method-ExploreDatasetParquet-clone}{\code{ExploreDatasetParquet$clone()}}
-}
-}
-\if{html}{\out{
-Inherited methods
+ \itemize{
+ \item \href{#method-ExploreDatasetParquet-initialize}{\code{ExploreDatasetParquet$new()}}
+ \item \href{#method-ExploreDatasetParquet-backend_kind}{\code{ExploreDatasetParquet$backend_kind()}}
+ \item \href{#method-ExploreDatasetParquet-enrichment}{\code{ExploreDatasetParquet$enrichment()}}
+ \item \href{#method-ExploreDatasetParquet-manifest}{\code{ExploreDatasetParquet$manifest()}}
+ \item \href{#method-ExploreDatasetParquet-source_dir}{\code{ExploreDatasetParquet$source_dir()}}
+ \item \href{#method-ExploreDatasetParquet-verify_source}{\code{ExploreDatasetParquet$verify_source()}}
+ \item \href{#method-ExploreDatasetParquet-all_pathways}{\code{ExploreDatasetParquet$all_pathways()}}
+ \item \href{#method-ExploreDatasetParquet-clone}{\code{ExploreDatasetParquet$clone()}}
+ }
+}
+\if{html}{\out{Inherited methods
-
}}
-\if{html}{\out{}}
-\if{latex}{\out{\hypertarget{method-ExploreDatasetParquet-new}{}}}
-\subsection{Method \code{new()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetParquet$new(input, config = NULL)}\if{html}{\out{
}}
+\if{html}{\out{}}
+\if{latex}{\out{\hypertarget{method-ExploreDatasetParquet-initialize}{}}}
+\subsection{\code{ExploreDatasetParquet$new()}}{
+ Read the parquet directory (manifest, obs, var, layers, varm, uns), build the config unless one
+ is given, prepare the feature and DE tables, and warn when the source `.h5ad` has changed since export.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetParquet$new(input, config = NULL)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{input}}{Path to the parquet directory.}
+ \item{\code{config}}{Optional pre-built config list; derived from `uns.json` when omitted.}
+ }
+ \if{html}{\out{
}}
+ }
}
-\subsection{Arguments}{
-\if{html}{\out{}}
-\describe{
-\item{\code{input}}{Path to the parquet directory.}
-
-\item{\code{config}}{Optional pre-built config list; derived from `uns.json` when
-omitted.}
-}
-\if{html}{\out{
}}
-}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetParquet-backend_kind}{}}}
-\subsection{Method \code{backend_kind()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetParquet$backend_kind()}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetParquet$backend_kind()}}{
+ Returns `"parquet"`.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetParquet$backend_kind()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetParquet-enrichment}{}}}
-\subsection{Method \code{enrichment()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetParquet$enrichment(contrast, kind)}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetParquet$enrichment()}}{
+ Enrichment results of one contrast and kind: reads the contrast's enrichment payload files on
+ first use, then defers to the `.h5ad` backend's implementation.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetParquet$enrichment(contrast, kind)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{contrast}}{Contrast name, one of `contrasts()`.}
+ \item{\code{kind}}{`"ora"` or `"gsea"`.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetParquet-manifest}{}}}
-\subsection{Method \code{manifest()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetParquet$manifest()}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetParquet$manifest()}}{
+ The parsed `manifest.json` of the parquet directory.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetParquet$manifest()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetParquet-source_dir}{}}}
-\subsection{Method \code{source_dir()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetParquet$source_dir()}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetParquet$source_dir()}}{
+ Path of the parquet directory.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetParquet$source_dir()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetParquet-verify_source}{}}}
-\subsection{Method \code{verify_source()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetParquet$verify_source(path = NULL)}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetParquet$verify_source()}}{
+ Compare the md5 of the source `.h5ad` with the one recorded in the manifest: `TRUE` when it
+ matches, `FALSE` when not, `NA` when there is nothing to check against.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetParquet$verify_source(path = NULL)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{path}}{Path to the source `.h5ad`; `NULL` (default) uses the path recorded in the manifest.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetParquet-all_pathways}{}}}
-\subsection{Method \code{all_pathways()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetParquet$all_pathways()}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetParquet$all_pathways()}}{
+ GO terms as in the base class, but an empty vector when clusterProfiler is not installed.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetParquet$all_pathways()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetParquet-clone}{}}}
-\subsection{Method \code{clone()}}{
-The objects of this class are cloneable with this method.
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetParquet$clone(deep = FALSE)}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetParquet$clone()}}{
+ The objects of this class are cloneable with this method.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetParquet$clone(deep = FALSE)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{deep}}{Whether to make a deep clone.}
+ }
+ \if{html}{\out{
}}
+ }
}
-\subsection{Arguments}{
-\if{html}{\out{}}
-\describe{
-\item{\code{deep}}{Whether to make a deep clone.}
-}
-\if{html}{\out{
}}
-}
-}
}
diff --git a/man/ExploreDatasetSE.Rd b/man/ExploreDatasetSE.Rd
index 4bde4dc..6124af1 100644
--- a/man/ExploreDatasetSE.Rd
+++ b/man/ExploreDatasetSE.Rd
@@ -9,8 +9,7 @@ reference and implements the accessor contract uniformly for every
SE shape. Concrete subclasses (`ExploreDatasetSE_RNASeq`,
`_CountQC`, `_CrisprCountQC`, `_Proteomics`) override two private
methods only:
-}
-\details{
+
- `.build_config(se)` — returns the per-instance config list at
`$initialize()` time
- `.prep()` — populates `private$.features_df`, `private$.de_dfs`,
@@ -20,174 +19,250 @@ This class is not instantiable on its own — instantiate a concrete
subclass instead.
}
\section{Super class}{
-\code{\link[exploreDE:ExploreDataset]{exploreDE::ExploreDataset}} -> \code{ExploreDatasetSE}
+\code{\link[exploreDE:ExploreDataset]{ExploreDataset}} -> \code{ExploreDatasetSE}
}
\section{Methods}{
\subsection{Public methods}{
-\itemize{
-\item \href{#method-ExploreDatasetSE-new}{\code{ExploreDatasetSE$new()}}
-\item \href{#method-ExploreDatasetSE-backend}{\code{ExploreDatasetSE$backend()}}
-\item \href{#method-ExploreDatasetSE-backend_kind}{\code{ExploreDatasetSE$backend_kind()}}
-\item \href{#method-ExploreDatasetSE-samples}{\code{ExploreDatasetSE$samples()}}
-\item \href{#method-ExploreDatasetSE-features}{\code{ExploreDatasetSE$features()}}
-\item \href{#method-ExploreDatasetSE-de}{\code{ExploreDatasetSE$de()}}
-\item \href{#method-ExploreDatasetSE-assay_names}{\code{ExploreDatasetSE$assay_names()}}
-\item \href{#method-ExploreDatasetSE-assay}{\code{ExploreDatasetSE$assay()}}
-\item \href{#method-ExploreDatasetSE-enrichment}{\code{ExploreDatasetSE$enrichment()}}
-\item \href{#method-ExploreDatasetSE-enrichment_input}{\code{ExploreDatasetSE$enrichment_input()}}
-\item \href{#method-ExploreDatasetSE-clone}{\code{ExploreDatasetSE$clone()}}
+ \itemize{
+ \item \href{#method-ExploreDatasetSE-initialize}{\code{ExploreDatasetSE$new()}}
+ \item \href{#method-ExploreDatasetSE-backend}{\code{ExploreDatasetSE$backend()}}
+ \item \href{#method-ExploreDatasetSE-backend_kind}{\code{ExploreDatasetSE$backend_kind()}}
+ \item \href{#method-ExploreDatasetSE-samples}{\code{ExploreDatasetSE$samples()}}
+ \item \href{#method-ExploreDatasetSE-features}{\code{ExploreDatasetSE$features()}}
+ \item \href{#method-ExploreDatasetSE-de}{\code{ExploreDatasetSE$de()}}
+ \item \href{#method-ExploreDatasetSE-assay_names}{\code{ExploreDatasetSE$assay_names()}}
+ \item \href{#method-ExploreDatasetSE-assay}{\code{ExploreDatasetSE$assay()}}
+ \item \href{#method-ExploreDatasetSE-enrichment}{\code{ExploreDatasetSE$enrichment()}}
+ \item \href{#method-ExploreDatasetSE-enrichment_input}{\code{ExploreDatasetSE$enrichment_input()}}
+ \item \href{#method-ExploreDatasetSE-clone}{\code{ExploreDatasetSE$clone()}}
+ }
}
-}
-\if{html}{\out{
-Inherited methods
+\if{html}{\out{Inherited methods
-
}}
-\if{html}{\out{}}
-\if{latex}{\out{\hypertarget{method-ExploreDatasetSE-new}{}}}
-\subsection{Method \code{new()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetSE$new(se, config = NULL)}\if{html}{\out{
}}
+\if{html}{\out{}}
+\if{latex}{\out{\hypertarget{method-ExploreDatasetSE-initialize}{}}}
+\subsection{\code{ExploreDatasetSE$new()}}{
+ Wrap a `SummarizedExperiment`: store it, build the config from it unless one is given, and
+ prepare the feature and DE tables.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetSE$new(se, config = NULL)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{se}}{A `SummarizedExperiment`.}
+ \item{\code{config}}{Optional pre-built config list; built from `se` by the subclass when `NULL`.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetSE-backend}{}}}
-\subsection{Method \code{backend()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetSE$backend()}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetSE$backend()}}{
+ The wrapped `SummarizedExperiment`.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetSE$backend()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetSE-backend_kind}{}}}
-\subsection{Method \code{backend_kind()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetSE$backend_kind()}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetSE$backend_kind()}}{
+ Returns `"se"`.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetSE$backend_kind()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetSE-samples}{}}}
-\subsection{Method \code{samples()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetSE$samples()}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetSE$samples()}}{
+ Sample metadata from `colData()`, with the SUSHI ` [Factor]` suffix stripped from column names,
+ rownames set to sample IDs, and a `Name` column added.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetSE$samples()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetSE-features}{}}}
-\subsection{Method \code{features()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetSE$features()}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetSE$features()}}{
+ Feature annotation table, prepared from `rowData()` by the subclass.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetSE$features()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetSE-de}{}}}
-\subsection{Method \code{de()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetSE$de(contrast)}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetSE$de()}}{
+ DE table of one contrast, prepared from `rowData()` by the subclass; an empty data.frame when
+ none was prepared. Errors on an unknown contrast.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetSE$de(contrast)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{contrast}}{Contrast name, one of `contrasts()`.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetSE-assay_names}{}}}
-\subsection{Method \code{assay_names()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetSE$assay_names()}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetSE$assay_names()}}{
+ Canonical assay names from the config's assay map whose SE assay exists; computed assays are
+ always included.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetSE$assay_names()}
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetSE-assay}{}}}
-\subsection{Method \code{assay()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetSE$assay(name, features = NULL, samples = NULL)}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetSE$assay()}}{
+ One assay as a features x samples matrix with rows renamed to feature IDs; `normalised_log2`,
+ `vst`, `fpkm` and `tpm` are computed when the config maps them to no SE assay.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetSE$assay(name, features = NULL, samples = NULL)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{name}}{Canonical assay name, one of `assay_names()`.}
+ \item{\code{features}}{Feature IDs (rows) to keep; `NULL` keeps all.}
+ \item{\code{samples}}{Sample IDs (columns) to keep; `NULL` keeps all.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetSE-enrichment}{}}}
-\subsection{Method \code{enrichment()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetSE$enrichment(contrast, kind)}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetSE$enrichment()}}{
+ Enrichment results of one kind, read from `metadata(se)` and flattened to a named list; an empty
+ list when absent. `contrast` is not used.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetSE$enrichment(contrast, kind)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{contrast}}{Contrast name; not used by this backend.}
+ \item{\code{kind}}{`"ora"` or `"gsea"`.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetSE-enrichment_input}{}}}
-\subsection{Method \code{enrichment_input()}}{
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetSE$enrichment_input(contrast)}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetSE$enrichment_input()}}{
+ Enrichment inputs read from `metadata(se)$enrichInput`, with `NULL` fields and no selections when
+ absent. `contrast` is not used.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetSE$enrichment_input(contrast)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{contrast}}{Contrast name; not used by this backend.}
+ }
+ \if{html}{\out{
}}
+ }
}
-}
\if{html}{\out{
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetSE-clone}{}}}
-\subsection{Method \code{clone()}}{
-The objects of this class are cloneable with this method.
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetSE$clone(deep = FALSE)}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetSE$clone()}}{
+ The objects of this class are cloneable with this method.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetSE$clone(deep = FALSE)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{deep}}{Whether to make a deep clone.}
+ }
+ \if{html}{\out{
}}
+ }
}
-\subsection{Arguments}{
-\if{html}{\out{}}
-\describe{
-\item{\code{deep}}{Whether to make a deep clone.}
-}
-\if{html}{\out{
}}
-}
-}
}
diff --git a/man/ExploreDatasetSE_CountQC.Rd b/man/ExploreDatasetSE_CountQC.Rd
index 1955b4b..cfff920 100644
--- a/man/ExploreDatasetSE_CountQC.Rd
+++ b/man/ExploreDatasetSE_CountQC.Rd
@@ -13,84 +13,84 @@ Inherits the accessor contract from [ExploreDataset] via
[ExploreDatasetSE]; overrides only `.build_config()` and `.prep()`.
}
\section{Super classes}{
-\code{\link[exploreDE:ExploreDataset]{exploreDE::ExploreDataset}} -> \code{\link[exploreDE:ExploreDatasetSE]{exploreDE::ExploreDatasetSE}} -> \code{ExploreDatasetSE_CountQC}
+\code{\link[exploreDE:ExploreDataset]{ExploreDataset}} -> \code{\link[exploreDE:ExploreDatasetSE]{ExploreDatasetSE}} -> \code{ExploreDatasetSE_CountQC}
}
\section{Methods}{
\subsection{Public methods}{
-\itemize{
-\item \href{#method-ExploreDatasetSE_CountQC-clone}{\code{ExploreDatasetSE_CountQC$clone()}}
+ \itemize{
+ \item \href{#method-ExploreDatasetSE_CountQC-clone}{\code{ExploreDatasetSE_CountQC$clone()}}
+ }
}
-}
-\if{html}{\out{
-Inherited methods
+\if{html}{\out{Inherited methods
-
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetSE_CountQC-clone}{}}}
-\subsection{Method \code{clone()}}{
-The objects of this class are cloneable with this method.
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetSE_CountQC$clone(deep = FALSE)}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetSE_CountQC$clone()}}{
+ The objects of this class are cloneable with this method.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetSE_CountQC$clone(deep = FALSE)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{deep}}{Whether to make a deep clone.}
+ }
+ \if{html}{\out{
}}
+ }
}
-\subsection{Arguments}{
-\if{html}{\out{}}
-\describe{
-\item{\code{deep}}{Whether to make a deep clone.}
-}
-\if{html}{\out{
}}
-}
-}
}
diff --git a/man/ExploreDatasetSE_CrisprCountQC.Rd b/man/ExploreDatasetSE_CrisprCountQC.Rd
index 7914f56..30e9caf 100644
--- a/man/ExploreDatasetSE_CrisprCountQC.Rd
+++ b/man/ExploreDatasetSE_CrisprCountQC.Rd
@@ -12,84 +12,84 @@ parsed from the SE feature IDs, which are assumed to follow the
Inherits `.prep()` from [ExploreDatasetSE_CountQC] unchanged.
}
\section{Super classes}{
-\code{\link[exploreDE:ExploreDataset]{exploreDE::ExploreDataset}} -> \code{\link[exploreDE:ExploreDatasetSE]{exploreDE::ExploreDatasetSE}} -> \code{\link[exploreDE:ExploreDatasetSE_CountQC]{exploreDE::ExploreDatasetSE_CountQC}} -> \code{ExploreDatasetSE_CrisprCountQC}
+\code{\link[exploreDE:ExploreDataset]{ExploreDataset}} -> \code{\link[exploreDE:ExploreDatasetSE]{ExploreDatasetSE}} -> \code{\link[exploreDE:ExploreDatasetSE_CountQC]{ExploreDatasetSE_CountQC}} -> \code{ExploreDatasetSE_CrisprCountQC}
}
\section{Methods}{
\subsection{Public methods}{
-\itemize{
-\item \href{#method-ExploreDatasetSE_CrisprCountQC-clone}{\code{ExploreDatasetSE_CrisprCountQC$clone()}}
+ \itemize{
+ \item \href{#method-ExploreDatasetSE_CrisprCountQC-clone}{\code{ExploreDatasetSE_CrisprCountQC$clone()}}
+ }
}
-}
-\if{html}{\out{
-Inherited methods
+\if{html}{\out{Inherited methods
-
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetSE_CrisprCountQC-clone}{}}}
-\subsection{Method \code{clone()}}{
-The objects of this class are cloneable with this method.
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetSE_CrisprCountQC$clone(deep = FALSE)}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetSE_CrisprCountQC$clone()}}{
+ The objects of this class are cloneable with this method.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetSE_CrisprCountQC$clone(deep = FALSE)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{deep}}{Whether to make a deep clone.}
+ }
+ \if{html}{\out{
}}
+ }
}
-\subsection{Arguments}{
-\if{html}{\out{}}
-\describe{
-\item{\code{deep}}{Whether to make a deep clone.}
-}
-\if{html}{\out{
}}
-}
-}
}
diff --git a/man/ExploreDatasetSE_Proteomics.Rd b/man/ExploreDatasetSE_Proteomics.Rd
index 4d3bf88..7fc4003 100644
--- a/man/ExploreDatasetSE_Proteomics.Rd
+++ b/man/ExploreDatasetSE_Proteomics.Rd
@@ -18,84 +18,84 @@ Inherits the accessor contract from [ExploreDataset] via
[ExploreDatasetSE]; overrides `.build_config()` and `.prep()`.
}
\section{Super classes}{
-\code{\link[exploreDE:ExploreDataset]{exploreDE::ExploreDataset}} -> \code{\link[exploreDE:ExploreDatasetSE]{exploreDE::ExploreDatasetSE}} -> \code{ExploreDatasetSE_Proteomics}
+\code{\link[exploreDE:ExploreDataset]{ExploreDataset}} -> \code{\link[exploreDE:ExploreDatasetSE]{ExploreDatasetSE}} -> \code{ExploreDatasetSE_Proteomics}
}
\section{Methods}{
\subsection{Public methods}{
-\itemize{
-\item \href{#method-ExploreDatasetSE_Proteomics-clone}{\code{ExploreDatasetSE_Proteomics$clone()}}
+ \itemize{
+ \item \href{#method-ExploreDatasetSE_Proteomics-clone}{\code{ExploreDatasetSE_Proteomics$clone()}}
+ }
}
-}
-\if{html}{\out{
-Inherited methods
+\if{html}{\out{Inherited methods
-
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetSE_Proteomics-clone}{}}}
-\subsection{Method \code{clone()}}{
-The objects of this class are cloneable with this method.
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetSE_Proteomics$clone(deep = FALSE)}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetSE_Proteomics$clone()}}{
+ The objects of this class are cloneable with this method.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetSE_Proteomics$clone(deep = FALSE)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{deep}}{Whether to make a deep clone.}
+ }
+ \if{html}{\out{
}}
+ }
}
-\subsection{Arguments}{
-\if{html}{\out{}}
-\describe{
-\item{\code{deep}}{Whether to make a deep clone.}
-}
-\if{html}{\out{
}}
-}
-}
}
diff --git a/man/ExploreDatasetSE_RNASeq.Rd b/man/ExploreDatasetSE_RNASeq.Rd
index 50e58d0..47d48d7 100644
--- a/man/ExploreDatasetSE_RNASeq.Rd
+++ b/man/ExploreDatasetSE_RNASeq.Rd
@@ -15,84 +15,84 @@ Inherits the accessor contract from [ExploreDataset] via
[ExploreDatasetSE]; overrides only `.build_config()` and `.prep()`.
}
\section{Super classes}{
-\code{\link[exploreDE:ExploreDataset]{exploreDE::ExploreDataset}} -> \code{\link[exploreDE:ExploreDatasetSE]{exploreDE::ExploreDatasetSE}} -> \code{ExploreDatasetSE_RNASeq}
+\code{\link[exploreDE:ExploreDataset]{ExploreDataset}} -> \code{\link[exploreDE:ExploreDatasetSE]{ExploreDatasetSE}} -> \code{ExploreDatasetSE_RNASeq}
}
\section{Methods}{
\subsection{Public methods}{
-\itemize{
-\item \href{#method-ExploreDatasetSE_RNASeq-clone}{\code{ExploreDatasetSE_RNASeq$clone()}}
+ \itemize{
+ \item \href{#method-ExploreDatasetSE_RNASeq-clone}{\code{ExploreDatasetSE_RNASeq$clone()}}
+ }
}
-}
-\if{html}{\out{
-Inherited methods
+\if{html}{\out{Inherited methods
-
}}
\if{html}{\out{}}
\if{latex}{\out{\hypertarget{method-ExploreDatasetSE_RNASeq-clone}{}}}
-\subsection{Method \code{clone()}}{
-The objects of this class are cloneable with this method.
-\subsection{Usage}{
-\if{html}{\out{}}\preformatted{ExploreDatasetSE_RNASeq$clone(deep = FALSE)}\if{html}{\out{
}}
+\subsection{\code{ExploreDatasetSE_RNASeq$clone()}}{
+ The objects of this class are cloneable with this method.
+ \subsection{Usage}{
+ \if{html}{\out{}}
+ \preformatted{ExploreDatasetSE_RNASeq$clone(deep = FALSE)}
+ \if{html}{\out{
}}
+ }
+ \subsection{Arguments}{
+ \if{html}{\out{}}
+ \describe{
+ \item{\code{deep}}{Whether to make a deep clone.}
+ }
+ \if{html}{\out{
}}
+ }
}
-\subsection{Arguments}{
-\if{html}{\out{}}
-\describe{
-\item{\code{deep}}{Whether to make a deep clone.}
-}
-\if{html}{\out{
}}
-}
-}
}