def extract_rna_info(chrom_info_file, raw_allelic_counts_dir, genotype_dir,time_step, target_regions_dir):
# make dictionary of identifier => index mapping
all_genotype_samples_file = genotype_dir + 'all_genotyped_samples.txt'
samp_idx = get_samples_index(all_genotype_samples_file)
# Initialize chromosome objects
chrom_list = chromosome.get_all_chromosomes(chrom_info_file)
chrom_dict = chromosome.get_chromosome_dict(chrom_info_file)
snp_files = SNPFiles(genotype_dir + 'snp_tab.h5',genotype_dir + 'snp_index.h5',genotype_dir+'haps.h5')
# STEP 1: make combined HDF5 files of AS counts,
# total mapped read counts, and genotype counts
individuals = get_individual_array(target_regions_dir + 'rna_seq_samples_' + str(time_step) + '.txt')
combined_files = CombinedFiles(raw_allelic_counts_dir, chrom_list,time_step)
for ind in individuals:
print(ind)
sample_id = ind + '_' + str(time_step)
count_files = CountFiles(raw_allelic_counts_dir, sample_id)
ind_idx = samp_idx[ind]
combined_files.add_counts(chrom_list, count_files, snp_files, ind_idx)
count_files.close()
return combined_files
def main():
sys.stderr.write("cmd: %s\n" % " ".join(sys.argv))
args = parse_args()
out_f = None
if args.output_file:
if args.output_file.endswith(".gz"):
out_f = gzip.open(args.output_file, "wt")
else:
out_f = open(args.output_file, "wt")
else:
out_f = sys.stdout
# make dictionary of identifier => index mapping
samp_idx = get_samples_index(args)
# read individuals
individuals = read_individuals(args, samp_idx)
chrom_list = chromosome.get_all_chromosomes(args.chrom)
chrom_dict = chromosome.get_chromosome_dict(args.chrom)
combined_files = CombinedFiles(OUTPUT_DIR, chrom_list)
snp_files = SNPFiles(args)
# STEP 1: make combined HDF5 files of AS counts,
# total mapped read counts, and genotype counts
sys.stderr.write("summing genotypes and read counts across individuals\n")
for ind in individuals:
# open count files for this indivudal
sys.stderr.write("individual: %s\n" % ind)
count_files = CountFiles(args.read_count_dir, ind)
ind_idx = samp_idx[ind]
# add counts to combined totals
combined_files.add_counts(chrom_list, count_files, snp_files, ind_idx)
count_files.close()
sys.stderr.write("generating list of target regions\n")
# STEP 2: generate list of target regions centered on test SNPs:
write_target_regions(out_f, args, chrom_list, combined_files, snp_files)
combined_files.close()
snp_files.close()
def main():
sys.stderr.write("cmd: %s\n" % " ".join(sys.argv))
args = parse_args()
out_f = None
if args.output_file:
if args.output_file.endswith(".gz"):
out_f = gzip.open(args.output_file, "wt")
else:
out_f = open(args.output_file, "wt")
else:
out_f = sys.stdout
# make dictionary of identifier => index mapping
samp_idx = get_samples_index(args)
# read individuals
individuals = read_individuals(args, samp_idx)
chrom_list = chromosome.get_all_chromosomes(args.chrom)
chrom_dict = chromosome.get_chromosome_dict(args.chrom)
combined_files = CombinedFiles(OUTPUT_DIR, chrom_list)
snp_files = SNPFiles(args)
# STEP 1: make combined HDF5 files of AS counts,
# total mapped read counts, and genotype counts
sys.stderr.write("summing genotypes and read counts across individuals\n")
for ind in individuals:
# open count files for this indivudal
sys.stderr.write("individual: %s\n" % ind)
count_files = CountFiles(args.read_count_dir, ind)
ind_idx = samp_idx[ind]
# add counts to combined totals
combined_files.add_counts(chrom_list, count_files, snp_files, ind_idx)
count_files.close()
sys.stderr.write("generating list of target regions\n")
# STEP 2: generate list of target regions centered on test SNPs:
write_target_regions(out_f, args, chrom_list, combined_files, snp_files)
combined_files.close()
snp_files.close()
def main():
options = parse_options()
util.info.write_info(sys.stdout, options)
gdb = genome.db.GenomeDB(assembly="hg19")
seq_track = gdb.open_track("seq")
chrom_dict = chromosome.get_chromosome_dict(options.chrom_file)
f = open(options.exon_file)
for line in f:
if line.startswith("#"):
continue
words = line.split()
gene_id = words[0]
gene_name = words[1]
chrom_name = words[2]
exon_num = int(words[3])
start = int(words[4])
end = int(words[5])
strand = int(words[6])
exon_len = end - start + 1
if exon_len < options.min_size:
start = start - (options.min_size - exon_len)/2
end = end + (options.min_size - exon_len)/2
sys.stderr.write("extended exon from %d bp to %d bp\n" %
(exon_len, end - start + 1))
seq_str = seq_track.get_seq_str(chrom_name, start, end)
sys.stdout.write(">%s exon %d\n%s\n" % (gene_name, exon_num, seq_str))
def main():
options = parse_options()
exon_out_f = open(options.exon_output_filename, "w")
gene_out_f = open(options.gene_output_filename, "w")
util.info.write_info(exon_out_f, options)
util.info.write_info(gene_out_f, options)
chrom_dict = chromosome.get_chromosome_dict(options.chrom_file)
gene_dict, tr_dict, gene_chrom_dict, tr_chrom_dict = \
gff.read_gff(options.gff, chrom_dict,
region_chrom=options.chrom,
region_start=options.start,
region_end=options.end)
gene_num = 0
for gene in gene_chrom_dict[options.chrom]:
exons = gene.get_merged_exons()
gene_num += 1
gene_out_f.write("%s %s %s %d %d %d %d\n" % (gene.gene_id, gene.gene_name,
gene.chrom.name, gene_num, gene.start,
gene.end, gene.strand))
exon_num = 0
if gene.strand == -1:
exons = exons[::-1]
for ex in exons:
exon_num += 1
exon_out_f.write("%s %s %s %d %d %d %d\n" %
(gene.gene_id, gene.gene_name, gene.chrom.name, exon_num,
ex.start, ex.end, gene.strand))
exon_out_f.close()
gene_out_f.close()
def main():
args = parse_args()
write_header(sys.stdout)
# find index of individual in list of samples
ind_idx = lookup_individual_index(args, args.individual)
data_files = DataFiles(args)
chrom_list = chromosome.get_all_chromosomes(args.chrom)
chrom_dict = chromosome.get_chromosome_dict(args.chrom)
genomewide_read_counts = get_genomewide_count(data_files.read_count_h5,
chrom_list)
if args.input_file.endswith(".gz"):
f = gzip.open(args.input_file)
else:
f = open(args.input_file)
line_count = 0
if args.target_region_size:
sys.stderr.write("setting target region size to %d\n" %
args.target_region_size)
for line in f:
line_count += 1
if line_count % 1000 == 0:
sys.stderr.write(".")
if line.startswith("#"):
continue
words = line.rstrip().split()
if words[1] == "NA":
# no SNP defined on this line:
write_NA_line(sys.stdout)
continue
chrom_name = words[0]
chrom = chrom_dict[chrom_name]
region_list = get_target_regions(args, chrom, words)
snp_pos = int(words[1])
snp_ref_base = words[3]
snp_alt_base = words[4]
# TODO: check that SNP ref/alt match?
snp_region = coord.Coord(chrom, snp_pos, snp_pos)
# pull out all of the SNPs in the target region(s)
region_snps = get_region_snps(data_files, region_list, ind_idx)
# pull out test SNP
test_snp_list = get_region_snps(data_files, [snp_region], ind_idx)
if len(test_snp_list) != 1:
test_snp = None
sys.stderr.write("WARNING: could not find test SNP at "
"position %s:%d\n" % (chrom.name, snp_pos))
het_snps = []
else:
test_snp = test_snp_list[0]
# pull out haplotype counts from linked heterozygous SNPs
het_snps = get_het_snps(region_snps)
set_snp_counts(data_files, region_list, het_snps, test_snp, args)
region_read_counts = get_region_read_counts(data_files, region_list)
write_output(sys.stdout, region_list, het_snps, test_snp, snp_pos,
region_read_counts, genomewide_read_counts)
sys.stderr.write("\n")
f.close()
data_files.close()
def main():
args = parse_args()
write_header(sys.stdout)
# find index of individual in list of samples
ind_idx = lookup_individual_index(args, args.individual)
data_files = DataFiles(args)
chrom_list = chromosome.get_all_chromosomes(args.chrom)
chrom_dict = chromosome.get_chromosome_dict(args.chrom)
genomewide_read_counts = get_genomewide_count(data_files.read_count_h5,
chrom_list)
unknown_chrom = set([])
if util.is_gzipped(args.input_file):
f = gzip.open(args.input_file, "rt")
else:
f = open(args.input_file, "r")
line_count = 0
if args.target_region_size:
sys.stderr.write("setting target region size to %d\n" %
args.target_region_size)
for line in f:
line_count += 1
if line_count % 1000 == 0:
sys.stderr.write(".")
if line.startswith("#"):
continue
words = line.rstrip().split()
if words[1] == "NA":
# no SNP defined on this line:
write_NA_line(sys.stdout)
continue
chrom_name = words[0]
if chrom_name in chrom_dict:
chrom = chrom_dict[chrom_name]
else:
if not chrom_name.startswith("chr"):
# try adding 'chr' to front of name
new_chrom_name = "chr" + chrom_name
if new_chrom_name in chrom_dict:
chrom_name = new_chrom_name
chrom = chrom_dict[chrom_name]
else:
# can't figure out this chromosome name
if not chrom_name in unknown_chrom:
unknown_chrom.add(chrom_name)
sys.stderr.write("WARNING: unknown chromosome '%s'")
continue
region_list = get_target_regions(args, chrom, words)
snp_pos = int(words[1])
snp_ref_base = words[3]
snp_alt_base = words[4]
# TODO: check that SNP ref/alt match?
snp_region = coord.Coord(chrom, snp_pos, snp_pos)
# pull out all of the SNPs in the target region(s)
region_snps = get_region_snps(data_files, region_list, ind_idx)
# pull out test SNP
test_snp_list = get_region_snps(data_files, [snp_region], ind_idx)
if len(test_snp_list) != 1:
test_snp = None
sys.stderr.write("WARNING: could not find test SNP at "
"position %s:%d\n" % (chrom.name, snp_pos))
het_snps = []
else:
test_snp = test_snp_list[0]
# pull out haplotype counts from linked heterozygous SNPs
het_snps = get_het_snps(region_snps)
set_snp_counts(data_files, region_list, het_snps, test_snp, args)
region_read_counts = get_region_read_counts(data_files, region_list)
write_output(sys.stdout, region_list, het_snps, test_snp, snp_pos,
region_read_counts, genomewide_read_counts)
sys.stderr.write("\n")
f.close()
data_files.close()
