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v0.0.1 #2

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merged 5 commits into from
May 7, 2022
Merged

v0.0.1 #2

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14960e3
pseudo code
sophie22 May 7, 2022
66b1737
read in file contents
sophie22 May 7, 2022
3070b64
identify exons then unique genes with suboptimal coverage
sophie22 May 7, 2022
0f8f510
write list of genes to file
sophie22 May 7, 2022
2ecc800
fromatting correction
sophie22 May 7, 2022
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identify exons then unique genes with suboptimal coverage
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@sophie22
sophie22 committed May 7, 2022
commit 3070b64036b7d478c05bd9f24fec08d77c690bd0
8 changes: 6 additions & 2 deletions genes_coverage.py
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Expand Up @@ -16,11 +16,15 @@

### Load sambamba output file contents into a DataFrame
sambamba_df = pd.read_csv(sambamba_file, sep='\t')
print(sambamba_df.columns)
print(sambamba_df.head())
# Split 'GeneSymbol;Accession' into separate columns
sambamba_df[["GeneSymbol", "Accession"]] = sambamba_df[
"GeneSymbol;Accession"].str.split(';', 1, expand=True)

### Identify exons with less than 100% coverage at 30x
below_threshold_exons_df = sambamba_df[sambamba_df[coverage_column] < 100.0]

### Identify unique genes with at least one exon with suboptimal coverage
below_threshold_genes = below_threshold_exons_df["GeneSymbol"].unique().tolist()
print(below_threshold_genes)

### Write gene symbols with suboptimal coverage to file