added copy number funciton

Author: alexandriai168

build/novartispdx/02-omics-novartispdx.py

@@ -47,4 +47,59 @@ def download_parse_omics_novPDX(synID:str , save_path:str = None, synToken:str =
     rnaseq_data = pd.read_excel(all_omics_excel, 'RNAseq_fpkm')
 
 
-    return(rnaseq_data, copy_number_data, mutations_data)
+    return(rnaseq_data, copy_number_data, mutations_data)
+
+
+def map_copy_number_novPDX(copy_number_data, improve_id_data, entrez_data):
+    """
+    Maps copy number data to improved sample id's and entrez gene data. Also does some data formatting.
+    
+    Parameters
+    ----------
+    copy_number_data : pd.Dataframe OR string
+        Pandas dataframe object with copy number data OR path to csv with copy number data
+
+    improve_id_data : pd.Dataframe OR string
+        Pandas dataframe object with improve id data OR path to csv with improve id data.  This is one of the outputs of parse_mmc2()
+
+    entrez_data : pd.Dataframe OR string
+        Pandas dataframe object with entrez gene data OR path to csv with entrez gene data.  Use this code to get this file: https://github.com/PNNL-CompBio/coderdata/tree/e65634b99d060136190ec5fba0b7798f8d140dfb/build/genes 
+
+    Returns
+    -------
+    sample_entrez_cn_df : pd.DataFrame
+        A DataFrame containing the mapped copy number data with columns: entrez_id, copy_number, copy_call, study, source ,improve_sample_id
+
+    """
+    # read in data
+    if isinstance(copy_number_data, pd.DataFrame) == False:
+        copy_number_data = pd.read_csv(copy_number_data)
+
+    if isinstance(improve_id_data, pd.DataFrame) == False:
+        improve_id_data = pd.read_csv(improve_id_data)
+    
+    if isinstance(entrez_data, pd.DataFrame) == False:
+        entrez_data = pd.read_csv(entrez_data)
+    
+    # melt dataframe so that there is gene name and improve_sample_id per row
+    long_cn_df = pd.melt(copy_number_data, id_vars=['Sample'], value_vars=copy_number_data.columns[copy_number_data.columns != 'Sample'])
+
+    # get entrez id's from Sample
+    entrez_cn_df = pd.merge(long_cn_df, entrez_data[['other_id','entrez_id']].drop_duplicates(), how = 'left', left_on= "Sample", right_on= "other_id")
+
+    # get copy call from value column (aka copy number)
+    entrez_cn_df['copy_call'] = [get_copy_call(a) for a in entrez_cn_df['value']]
+    
+    # get improve sample id
+    improve_id_data['to_merge'] = improve_id_data['common_name'].str.replace("NIBR","")
+    sample_entrez_cn_df = pd.merge(entrez_cn_df.drop_duplicates(), improve_id_data[['to_merge','improve_sample_id']].drop_duplicates(), how = 'left', left_on= "variable", right_on= "to_merge")
+
+    # clean up columns and data types
+    sample_entrez_cn_df = sample_entrez_cn_df.drop(columns=['Sample','variable','other_id','to_merge'])
+    sample_entrez_cn_df['source'] = "CPDM"
+    sample_entrez_cn_df['study'] = "novartispdx"
+    sample_entrez_cn_df = sample_entrez_cn_df.rename(columns={'value':'copy_number'})
+    sample_entrez_cn_df = sample_entrez_cn_df.astype({'entrez_id':'int','improve_sample_id':'int'})
+    sample_entrez_cn_df = sample_entrez_cn_df[['entrez_id','copy_number','copy_call','study','source','improve_sample_id']]
+    
+    return(sample_entrez_cn_df)