def repl():
running = True
while(running):
command = raw_input(prompt)
if command == "count bases":
base_tuple = count_bases(file)
print "A: " + str(base_tuple[0]) + " C: " + str(base_tuple[1]) + " G: " + str(base_tuple[2]) + " T: " + str(base_tuple[3])
print "GC%: " + str(base_tuple[4])
elif command == "exit":
running = False
exit()
elif command == "graph base count":
print "Counting bases...",
base_tuple = count_bases(file)
print "Done."
graph_base_count(base_tuple[0], base_tuple[1], base_tuple[2], base_tuple[3])
elif command == "help":
help()
elif command == "print description":
print file_description
else:
print "Command not found. Try again or type \"help\" for help."
def process_pileups(bamfile, snp_d, read_checklist):
N = len(snp_d)
i = 1.0
for k in snp_d:
if (i*100/N) % 5 == 0:
sys.stderr.write('%s: %i SNPs processed (%i%%)\n' % (get_timestamp(), i, i/N * 100))
i += 1.0
snp = snp_d[k][0]
snp.test += 1
base_count = {'A': 0, 'C': 0, 'G': 0, 'T': 0, 'U': 0, 'N': 0,
'low_qual': 0, 'del': 0, 'mates_disagree': 0, 'unique_reads': 0}
reads_at_pos = dict(zip(base_count.keys(), [[] for key in base_count.keys()]))
valid_reads = []
# print snp.get_region(k[0])
for col in bamfile.pileup(region=snp.get_region(k[0])):
if snp.pos_0 == col.pos:
base_count, weighted, valid_reads, reads_at_pos = count_bases(col)
break
if base_count is None or reads_at_pos is None:
print 'Skipping', snp.get_region(k[0])
continue
snp.add_pileup(base_count, reads_at_pos)
# print 'V', valid_reads
valid_reads = set([(read, base==snp.mutation)
for read, base, seq, qpos in valid_reads
if base in (snp.refbase, snp.mutation)])
read_checklist.update(valid_reads)
# This is a simulation to see how ambiguous SNPs can be removed from the read count
# print snp_d.keys()
# snp_d[('Chr4', 10952350)][0].r_support_mutation.append('HWI-ST377:127:D0PHGACXX:7:1306:11252:6941')
# read_checklist.add(('HWI-ST377:127:D0PHGACXX:7:1306:11252:6941', True))
# print 'x', sorted(snp_d[('Chr4', 10952350)][0].r_support_refbase[:10])
# print 'x', sorted(snp_d[('Chr4', 10951240)][0].r_support_refbase[:10])
filtered_reads = set(filter_ambiguous_reads(read_checklist))
# print len(read_checklist), len(filtered_reads)
for k in snp_d:
snp = snp_d[k][0]
if snp.is_covered:
snp.cleanse_counts(filtered_reads)
pass
def analyse_snps(bamfile, snpfile_open, hit_mode, refpath=None, mult_counts=None, with_seqs=False, out=sys.stdout):
header = ['', 'Pos_SNP', '#UniqueReads', '#Hits', '#Reads_Col', '#Reads_Ped', '#Score_Col', '#Score_Ped',
'#Reads_N', '#Reads_lowqual', '#Reads_del', '#Reads_other']
if hit_mode == 'intra':
header[0] = 'AGI'
elif hit_mode == 'inter':
header[0] = 'Contig'
else:
sys.stderr.write('Wrong mode: %s. Exiting.\n' % hit_mode)
sys.exit(1)
if refpath is not None:
header.extend(['#match', '#bases', 'MAP_ERR'])
if with_seqs:
header.extend(['primer_col', 'primer_ped'])
out.write(','.join(map(str, header)) + '\n')
reads_per_gene = {}
contig = None
for line in snpfile_open:
snp = line.strip().split('\t')
attributes = dict([attr.split('=') for attr in snp[8].split(';')])
# next two if-conditions should always be False with new snp data
# schedule for removal?
if attributes['refbase'] not in 'ACGTU':
continue
if attributes['mutation'] not in 'ACGTU':
continue
refseq = None
if refpath is not None:
if contig is None or snp[0] != contig:
ref_fn = os.path.join(refpath, 'TAIR10_chr%c.fas' % snp[0][-1])
refseq = read_fasta(open(ref_fn, 'rb'))
contig, start, end = snp[0], int(snp[3]), int(snp[4])
region = '%s:%i-%i' % (contig, start, end)
base_count = None
flank_counts = []
for col in bamfile.pileup(region=region):
if start == col.pos:
base_count, weighted, valid_reads = count_bases(col, mult_counts=mult_counts)
elif refseq is not None:
count, dummy, valid_reads_flank = count_bases(col, mult_counts=mult_counts)
try:
# this needs to be in a try-block because there might be ambiguity codes... ><;
flank_counts.append((count[refseq[col.pos]], len(valid_reads_flank)))
except:
pass
pass
if base_count is not None:
row = [None, end,
base_count['unique_reads'],
sum(base_count.values()) - (base_count['unique_reads'] + base_count['del']),
base_count[attributes['refbase']],
base_count[attributes['mutation']],
weighted[attributes['refbase']],
weighted[attributes['mutation']],
base_count['N'],
base_count['low_qual'],
base_count['del'],
sum([base_count[v] for v in 'ACGT']) - \
(base_count[attributes['refbase']] + base_count[attributes['mutation']])]
if refpath is not None:
n_matches, n_bases = reduce(lambda x,y: (x[0]+y[0], x[1]+y[1]), flank_counts)
mapping_error = 1.0 - (float(n_matches) / n_bases)
row.extend([n_matches, n_bases, mapping_error])
if hit_mode == 'intra':
row[0] = attributes['gene_ID']
rpg_key = row[0]
elif hit_mode == 'inter':
row[0] = contig
rpg_key = '%s:%i' % (contig, end)
else:
sys.stderr.write('Wrong mode: %s. Exiting.\n' % hit_mode)
sys.exit(1)
# list-set-list asserts that reads that cover multiple snps within the same gene
# are only counted once (unless they disagree at different snp-sites,
# which is a different problem)
seqs = [(seq, qpos, base==attributes['mutation'])
for read, base, seq, qpos in valid_reads
if base in (attributes['refbase'], attributes['mutation'])
and seq is not None]
# colseq, pedseq = get_best_read_sequence(seqs)
if with_seqs:
colseq, pedseq = get_primer_sequence(seqs)
row.extend([colseq, pedseq])
out.write(','.join(map(str, row)) + '\n')
valid_reads = list(set([(read, rpg_key, base==attributes['mutation'])
for read, base, seq, qpos in valid_reads
if base in (attributes['refbase'], attributes['mutation'])]))
if len(valid_reads) == 0:
continue
if rpg_key in reads_per_gene:
# reads_per_gene[attributes['gene_ID']] = reads_per_gene[attributes['gene_ID']].union(valid_reads)
reads_per_gene[rpg_key].extend(valid_reads)
else:
reads_per_gene[rpg_key] = valid_reads
pass
pass
pickle.dump(reads_per_gene, open(os.path.basename(bamfile.filename) + '.' + hit_mode + '.rpg.full.dat', 'wb'))
reads_per_gene = count_reads_per_gene(reads_per_gene)
# if hit_mode == 'intra':
pickle.dump(reads_per_gene, open(os.path.basename(bamfile.filename) + '.' + hit_mode + '.rpg.dat', 'wb'))
bamfile.close()
# return analysed_snps, reads_per_gene
pass
