Script for detecting mutations in aligned reads (.bam |.sam) e.g. from RNA base conversion techniques such as TimeLapse, SLAM-seq, TUC-seq

Usage:
python detect-mutations.py -b <file.bam> [-s <snpFile.txt>] [--reads <PE|SE>] [--mutType <TC[,GA,..]> ][--minDist <int>] [--minQual <int>] [--tracks] [--mutPos]

Requires: pysam

Options:

    -b|--bam    path to input .bam file
    -s|--SNP    path to file with SNPs positions
    --mutType   list of mutations types to analyze comma-separated (defalut: TC)
    --reads     type of reads paird-end (PE) or single end (SE) (default: PE)
    --minDist   smallest allowed distance of mutation for either 5' or 3' end of read
    --minQual   smallest allowed sequencing quality of mutation
    --tracks    make .bedGraph tracks of mutations
    --mutPos    make _cB.csv file with mutation statisctics for every nucleotide

Input:

• .bam file
• list of SNPs for common mutations removal (optional) Format: chrom:position:REF:MUT

Output:

• *_counts.csv - mutation statistics for each read or read pair
  • qname : read (pair) name
  • nA : number of A in reference sequence covered by the read
  • nC : number of C
  • nT : number of T
  • nG : number of G,
  • rname : chromosome
  • FR : forward or reverse strand
  • sj : read (pair) contains splice junction
  • TA : number of T -> A conversions recorded in read (pair)
  • CA
  • GA
  • NA
  • AT
  • CT
  • GT
  • NT
  • AC
  • TC
  • GC
  • NC
  • AG
  • TG
  • CG
  • NG
  • AN
  • TN
  • CN
  • GN
• *_cB.csv - mutation statistics for each nucleotide position. Coverage + number of mutations observed
  • rname : chromosome name
  • gloc : genomic position of nucleotide
  • trials : number of reads that recorded given nucleotide
  • n : number of mutations observed at nucleotide
• *_muts.bedGraph - browser tracks for viewing mutation counts
  • chromosome name
  • nucleotide start, end
  • count of mutations at position