genewiseMAFC.py

genewiseMAFC.enrichASE(args)[source]

identify genes with differential expression between two alleles

requires: annotated SNP data (*.merged.csv) output from bedtools intersect

How it works:
  1. group SNPs together by gene
  2. For each SNP in that gene, calculate the absolute(log2(fold change))
  3. take the average of absolute(log2(fold change)) values across all SNPS for that gene
  4. filter on:
    • average read depth at variable positions for the gene
    • number of SNPs in the gene
    • average(absolute(log2(fold change))) for the gene
Two optional args with no defaults change the program behaviour:
  1. –output <file> sends the results to file rather than stdout
  2. –gene <gene> yields data for every SNP in a specific gene. Without this arg, the program produces instead a summary table of all significant genes in order of priority (sorted by: average(absolute(log2(fold change))))
genewiseMAFC.meanAbsoluteFoldChange(frame)[source]

find the average log2 fold change of SNPs (alleles) for a single gene