Calculate Depth of Coverage and Breadth of Coverage from a bam file. This function calculates by chromsome and for the entire genome. Additionally, if the mtchr (Mitochondrial chromosome name) is provided, nuclear coverage and the ratio of mtDNA:nuclear DNA is calculated. #bam #stats

## depth_of_coverage.py
#
# This script calculates the depth of coverage and breadth of coverage for a given bam.
# Outputs a dictionary containing the contig/chromosome names and the depth and breadth of coverage for each
# and for the entire genome.
#
# If you optionally specify the name of the mitochondrial chromosome (e.g. mtDNA, chrM, chrMT)
# The script will also generate breadth and depth of coverage for the nuclear genome AND the ratio
# of mtDNA:nuclearDNA; which can act as a proxy in some cases for mitochondrial count within an individual.
#
# Author: Daniel E. Cook
# Website: Danielecook.com
#


import os
import re
from subprocess import Popen, PIPE

def get_contigs(bam):
    header, err = Popen(["samtools","view","-H",bam], stdout=PIPE, stderr=PIPE).communicate()
    if err != "":
        raise Exception(err)
    # Extract contigs from header and convert contigs to integers
    contigs = {}
    for x in re.findall("@SQ\WSN:(?P<chrom>[A-Za-z0-9_]*)\WLN:(?P<length>[0-9]+)", header):
        contigs[x[0]] = int(x[1])
    return contigs

def coverage(bam, mtchr = None):
    # Check to see if file exists
    if os.path.isfile(bam) == False:
        raise Exception("Bam file does not exist")
    contigs = get_contigs(bam)

    # Guess mitochondrial chromosome
    mtchr = [x for x in contigs if x.lower().find("m") == 0]
    if len(mtchr) != 1:
        mtchr = None
    else:
        mtchr = mtchr[0]

    coverage_dict = {}
    for c in contigs.keys():
        command = "samtools depth -r %s %s | awk '{sum+=$3;cnt++}END{print cnt \"\t\" sum}'" % (c, bam)
        coverage_dict[c] = {}
        coverage_dict[c]["Bases Mapped"], coverage_dict[c]["Sum of Depths"] = map(int,Popen(command, stdout=PIPE, shell = True).communicate()[0].strip().split("\t"))
        coverage_dict[c]["Breadth of Coverage"] = coverage_dict[c]["Bases Mapped"] / float(contigs[c])
        coverage_dict[c]["Depth of Coverage"] = coverage_dict[c]["Sum of Depths"] / float(contigs[c])
        coverage_dict[c]["Length"] = int(contigs[c])

    # Calculate Genome Wide Breadth of Coverage and Depth of Coverage
    genome_length = float(sum(contigs.values()))
    coverage_dict["genome"] = {}
    coverage_dict["genome"]["Length"] = int(genome_length)
    coverage_dict["genome"]["Bases Mapped"] = sum([x["Bases Mapped"] for k, x in coverage_dict.iteritems() if k != "genome"])
    coverage_dict["genome"]["Sum of Depths"] = sum([x["Sum of Depths"] for k, x in coverage_dict.iteritems() if k != "genome"])
    coverage_dict["genome"]["Breadth of Coverage"] = sum([x["Bases Mapped"] for k, x in coverage_dict.iteritems() if k != "genome"]) / float(genome_length)
    coverage_dict["genome"]["Depth of Coverage"] = sum([x["Sum of Depths"] for k, x in coverage_dict.iteritems() if k != "genome"]) / float(genome_length)

    if mtchr != None:
        # Calculate nuclear breadth of coverage and depth of coverage
        ignore_contigs = [mtchr, "genome", "nuclear"]
        coverage_dict["nuclear"] = {}
        coverage_dict["nuclear"]["Length"] = sum([x["Length"] for k,x in coverage_dict.iteritems() if k not in ignore_contigs ])
        coverage_dict["nuclear"]["Bases Mapped"] = sum([x["Bases Mapped"] for k, x in coverage_dict.iteritems() if k not in ignore_contigs])
        coverage_dict["nuclear"]["Sum of Depths"] = sum([x["Sum of Depths"] for k, x in coverage_dict.iteritems() if k not in ignore_contigs])
        coverage_dict["nuclear"]["Breadth of Coverage"] = sum([x["Bases Mapped"] for k, x in coverage_dict.iteritems() if k not in ignore_contigs]) / float(coverage_dict["nuclear"]["Length"])
        coverage_dict["nuclear"]["Depth of Coverage"] = sum([x["Sum of Depths"] for k, x in coverage_dict.iteritems() if k not in ignore_contigs]) / float(coverage_dict["nuclear"]["Length"])

        # Calculate the ratio of mtDNA depth to nuclear depth
        coverage_dict["genome"]["mt_ratio"] = coverage_dict[mtchr]["Depth of Coverage"] / float(coverage_dict["nuclear"]["Depth of Coverage"])

    # Flatten Dictionary
    coverage = []
    for k,v in coverage_dict.items():
        for x in v.items():
            coverage += [(k,x[0], x[1])]
    return coverage