def main(config_file):
with open(config_file) as in_handle:
config = yaml.load(in_handle)
region_size = int(config["algorithm"]["region_size"])
num_regions = int(config["algorithm"]["num_regions"])
bam_files = prepare_bam_files(config)
regions = counts.random_regions(bam_files[0].all_regions(),
num_regions, region_size)
values = []
for i, bam1 in enumerate(bam_files):
for bam2 in bam_files[i+1:]:
values.extend(compare_bam_files(bam1, bam2, regions))
scatter_plot(values, bam1.name, bam2.name, region_size,
config["files"]["coverage_pdf"])
def main(config_file):
with open(config_file) as in_handle:
config = yaml.load(in_handle)
picard = PicardRunner(config["program"]["picard"])
bams = [NormalizedBam(align["name"], align["file"], picard)
for align in config["alignments"]]
for rconfig in config["regions"]:
with open(rconfig["file"]) as in_handle:
assert rconfig["name"] == "CES"
regions = read_ces_regions(in_handle, rconfig["size"])
rregions = random_regions(regions, rconfig["random"], rconfig["size"])
counts = region_counts(bams, regions, rconfig["name"])
rcounts = region_counts(bams, rregions, "background")
out_file = "%s-distribution%s.pdf" % (rconfig["name"],
"-smoothed" if rconfig["smoothed"] else "")
plot_count_distribution(out_file, counts + rcounts, rconfig["smoothed"])
