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Achievement: Pull Sharkx2Achievement: Quickdraw

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Thokas99/README.md

About Me

Computational biologist with experience in single-cell and multi-omics analysis of cancer biology. Skilled in scRNA-seq, bulk RNA-seq, miRNA-seq, DNA methylation, immune deconvolution, machine learning, and statistical modelling. Experienced in investigating tumour cell plasticity, malignant state transitions, immune phenotypes, genomic instability, and treatment response across lung cancer and haematological malignancies. Strong background in building reproducible R and Python workflows and translating high-dimensional molecular data into biologically and interpretable findings.

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  1. Acute_Lymphoid_Leukemia_Project Acute_Lymphoid_Leukemia_Project Public

    Forked from iamandreatonina/Acute_Lymphoid_Leukemia_Project

    HTML

  2. simple-nextflow-salmon simple-nextflow-salmon Public

    Plug-and-play Nextflow workflow for paired-end bulk RNA-seq quantification with Salmon, tximport, FastQC, and MultiQC.

    Python

  3. Useful_code Useful_code Public

    My own usefull code

    R

  4. veryMAD veryMAD Public

    veryMAD is a small R package for transparent median absolute deviation (MAD) scaling and auditable quality-control flagging across bulk, single-cell, and other observation-level omics metadata.

    R

  5. ComBat-refQL ComBat-refQL Public

    Forked from xiaoyu12/Combat-ref

    An extended implementation of ComBat-ref using edgeR quasi-likelihood modeling for robust batch correction of RNA-seq count data.

    R