def alnDict2output(aln_dict, dn, order='sorting'):
info = []
if len(aln_dict) == 0:
cmn.run('touch %s' % dn)
return None
#maxLength = max([len(each) for each in aln_dict.keys()])
maxLength = 0
maxNameLength = max([len(each) for each in aln_dict])
nameformat = '{:<%s}' % maxNameLength
names = list(aln_dict.keys())
if order == 'sorting':
names = sorted(names, key=lambda x: number4sorting(aln_dict[x]))
elif order == 'grouping':
#this is used to output inconsistent group
#rank by grouping of species IDs
names = sorted(names, key=lambda x: group_by_spnames(x))
else:
names.sort()
for i, name in enumerate(names):
#name = 'readgroup%s' % i
aln = aln_dict[name]
name = nameformat.format(name)
toAdd = maxLength - len(aln)
if toAdd > 0:
aln += '-' * toAdd
info.append('%s %s\n' % (name, ''.join(aln)))
cmn.write_file(''.join(info), dn)
def read_baits(fn):
adict = {}
toAdd = {}
hasPrimer = True
new = []
for line in cmn.file2lines(fn):
if line.strip() == '':
continue
sp, name, seq = line.split()
print(len(seq))
if len(seq) != 698:
hasPrimer = False
if len(seq) == 658:
#fixable
seq = add_primer(seq)
else:
print('Error! didn\'t recognize the length of the bait %s %s' %
(sp, name))
sys.exit()
newline = '%s\t%s\t%s\n' % (sp, name, seq)
new.append(newline)
key = '%s_%s' % (sp, name)
adict[key] = seq
toAdd[name] = seq
if not hasPrimer:
print('revise the input baits to add primer...')
cmn.write_file(''.join(new), fn)
return adict, toAdd
def prune_tree(ftree, fseq):
t = ete3.Tree(ftree)
IDlist = cmn.cmd2lines('grep ">" %s|cut -d ">" -f 2' % fseq)
t.prune(IDlist)
dn = 'prune_tree.tre'
cmn.write_file(t.write(format=1), dn)
return dn
def makeBlastDatabase(seqDict):
dn = 'db4picking.fa'
new = ['>%s\n%s\n' % (name, seqDict[name])
for name in seqDict
if seqDict[name].strip('N-X') != '']
cmn.write_file(''.join(new), dn)
cmd = 'module add blast; makeblastdb -dbtype=nucl -in=%s' % dn
cmn.run(cmd)
return dn
def do_barcode_blast(sequence):
fdb = '/project/biophysics/Nick_lab/wli/sequencing/scripts/data/barcodes/species_barcodes_4mapping.fa'
#fdb = '/project/biophysics/Nick_lab/wli/sequencing/scripts/data/barcodes/all_barcodes_NoN_0.95.fasta'
namelabel = sequence.split()[0][1:].split()[0].split('|')[0].replace('*','').split('[')[0].replace('"','').replace("'", '')
fquery = '/tmp/%s.fa' % namelabel
cmn.write_file(sequence, fquery)
cmd = 'module add blast; blastn -query %s -db %s ' % (fquery, fdb)
cmd += '-outfmt \'6 sseqid qlen slen length pident\''
lines = cmn.cmd2lines(cmd)
#cmn.run('rm %s' % fquery)
return lines
def update_baits(bait_dict):
adict = {}
for i, name in enumerate(bait_dict):
fnlabel = 'bait%s' % i
dn = 'baits/%s.fa' % fnlabel
seq = bait_dict[name]
fasta = '>%s\n%s\n' % (name, ''.join(seq))
cmn.write_file(fasta, dn)
cmd = 'module add bwa; bwa index %s -p %s' % (dn, fnlabel)
cmn.run(cmd)
adict[name] = dn
return adict
def output_matrix(arr, fn=None):
dimension = arr.ndim
lines = []
for index, content in np.ndenumerate(arr):
first = ''
for i in range(dimension):
first += '%s\t' % (index[i])
lines += ['%s%s' % (first, content)]
if fn != None:
cmn.write_file('\n'.join(lines), fn)
else:
return '\n'.join(lines)
def parse_inserted_gap(ID, seq, label):
fn = 'sampleRun_%s/bait_insertion' % ID
#if cmn.filexist(fn) or ('N' in seq.replace('-', 'N').strip('N')):
if cmn.filexist(fn):
#lines = cmn.file2lines(fn)
#lines = sorted(lines, key=lambda x: int(x.split(',')[0][1:]))
#Ngap = 0
#for line in lines:
# items = line.strip().split()
# Ngap += len(items[-1])
#check what is the right range of sequence
print('runing blast to fix %s' % ID)
checkSeq = seq.replace('-', 'N').strip('N')
fquery = 'tmpInput.fa'
fasta = '>input\n%s\n' % checkSeq
cmn.write_file(fasta, fquery)
dn = 'tmpBr_%s.txt' % label
cmd = 'blastn -query %s -db /project/biophysics/Nick_lab/wli/sequencing/scripts/data/barcodes/all_barcodes_4verify.fa ' % fquery
cmd += '-task blastn-short -dust no -outfmt \'6 qseqid sseqid qstart qend sstart send evalue pident qseq sseq\' -out %s' % dn
cmn.run(cmd)
isFixed = False
for line in cmn.file2lines(dn):
items = line.strip().split()
#print items
qstart, qend, sstart, send = list(map(int, items[2:6]))
if sstart == 1 and send == 658 and qstart == 21:
qseq, sseq = items[-2:]
new = [
char1 for char1, char2 in zip(qseq, sseq) if char2 != '-'
]
if len(new) == 658:
seq = seq[:qstart - 1] + ''.join(new) + seq[qend:]
print('solution found for %s' % ID)
isFixed = True
break
if sstart == 2 and send == 655 and qstart == 22:
qseq, sseq = items[-2:]
new = [
char1 for char1, char2 in zip(qseq, sseq) if char2 != '-'
]
if len(new) == 654:
seq = seq[:qstart - 1] + ''.join(new) + seq[qend:]
print('solution found for %s' % ID)
isFixed = True
break
if not isFixed:
cmn.append_file('%s\t%s\n' % (ID, label), 'cannot_fixed_indel.txt')
return seq
def parse_ref(seqDict):
cmn.mkdir('baits')
newDict = {}
for i, name in enumerate(seqDict):
seq = seqDict[name]
fnlabel = 'bait%s' % i
dn = 'baits/%s.fa' % fnlabel
name = name.replace('*', '').replace('"', "'")
fasta = '>%s\n%s\n' % (name, seq)
cmn.write_file(fasta, dn)
cmd = 'module add bwa; bwa index %s -p %s' % (dn, fnlabel)
cmn.run(cmd)
newDict[name] = dn
return newDict
def do_barcode_blast(sequence, seqDict):
#fref = '/project/biophysics/Nick_lab/wli/sequencing/scripts/data/barcodes/species_barcodes_4mapping.fa'
#fadd = '/project/biophysics/Nick_lab/wli/sequencing/scripts/data/barcodes/added_from_customBaits.baitInfo'
fdb = makeBlastDatabase(seqDict)
#fdb = '/project/biophysics/Nick_lab/wli/sequencing/scripts/data/barcodes/all_barcodes_NoN_0.95.fasta'
namelabel = sequence.split()[0][1:].split()[0].split('|')[0].replace('*','').split('[')[0].replace('"','').replace("'", '')
namelabel = namelabel.replace('/', '_')
fquery = '/tmp/%s.fa' % namelabel
cmn.write_file(sequence, fquery)
cmd = 'module add blast; blastn -query %s -db %s ' % (fquery, fdb)
cmd += '-outfmt \'6 sseqid qlen slen length pident\''
lines = cmn.cmd2lines(cmd)
cmn.run('rm %s' % fquery)
return lines
def get_mash_file(name, seq):
global mash_file_dict, cpu
try:
fn = mash_file_dict[name]
except KeyError:
fn = '/tmp/%s' % name
seq = ''.join(seq).replace('-', '').replace('N', '')
fasta = '>%s\n%s\n' % (name, seq)
cmn.write_file(fasta, fn)
cmd = '/home2/wli/local/mash-Linux64-v1.1.1/mash sketch -n -p %s %s' % (
cpu, fn)
cmn.run(cmd)
dn = fn + '.msh'
mash_file_dict[name] = dn
fn = dn
return fn
def do_barcode_blast(sequence):
fdb = '/project/biophysics/Nick_lab/wli/sequencing/scripts/data/barcodes/all_barcodes_4verify.fa'
namelabel = sequence.split()[0][1:].split()[0].split('|')[0].replace('*','').split('[')[0].replace('"','').replace("'", '').split('(')[0].split('/')[0].split('\\')[0]
fquery = '/tmp/%s.fa' % namelabel
cmn.write_file(sequence, fquery)
fbr = fquery + '.br'
cmd = 'module add blast; blastn -max_target_seqs 5000 -query %s -db %s -ungapped ' % (fquery, fdb)
cmd += '-outfmt \'6 sseqid slen length pident qstart qend qseq sseq\''
cmd += ' -out %s ' % fbr
#print cmd
cmn.run(cmd)
#cmd += ' | head -n 10'
#lines = cmn.cmd2lines(cmd)
lines = cmn.file2lines(fbr)
cmn.run('rm %s' % fquery)
cmn.run('rm %s' % fbr)
return lines
def make_index_header(fvcf, flen):
lendict = read_length_info(flen)
ordered_scafs = []
taken = set([])
with open(fvcf) as fp:
for line in fp:
if not line.startswith('scaffold'):
continue
scaf = line.split()[0]
if scaf not in taken:
taken.add(scaf)
ordered_scafs.append(scaf)
info = []
for scaf in ordered_scafs:
length = lendict[scaf]
for i in range(length):
info.append('%s\t%s\n' % (scaf, (i+1)))
dn = 'index_header'
cmn.write_file(''.join(info), dn)
def check_difference(seq1, seq2):
print(len(seq1), len(seq2))
if len(seq1) == len(seq2):
return sum([char1 != char2 for char1, char2 in zip(seq1, seq2)
if char1 not in gapChars and char2 not in gapChars])
cmn.write_file(seq1, 'tmpSeq1.fa')
cmn.write_file(seq2, 'tmpSeq2.fa')
info = cmn.cmd2info('blastn -query tmpSeq1.fa -subject tmpSeq2.fa')
#Identities = 656/656 (100%)
identityString = cmn.find_between(info, 'Identities = ', ' (')
identN, totalN = list(map(int, identityString.split('/')))
cmn.write_file(info, 'checkTmp%s.br' % (ID))
return totalN - identN
try:
fn = sys.argv[1]
except:
print("Usage: *.py", file=sys.stderr)
sys.exit()
N = 1000000 #get this much positions
label = '%sM' % (N / 1000000)
seqDict, length = read_fa(fn)
if length < N:
print('sequence length is shorter than 10K, exist!')
sys.exit()
positions = random.sample(list(range(length)), N)
positions.sort()
new = []
for name in seqDict:
seq = seqDict[name]
newSeq = [seq[i] for i in positions]
fasta = '>%s\n%s\n' % (name, ''.join(newSeq))
new.append(fasta)
dn = cmn.lastName(fn).replace('.fasta', '').replace(
'.fa', '') + '_rd%s.fa' % (label)
cmn.write_file(''.join(new), dn)
hasCombined = True
if len(old_fastqs) == 0: # no old data
print('no old libs found for %s' % label)
cmn.run('ln -s %s' % dn)
else: #has old data
print('combining old libs for %s' % label)
old_fastqs, dup_fastqs = remove_duplication(old_fastqs)
cmn.run('cp %s %s' % (dn, wdir))
log_info.append('%s\t%s\n' % (label, dn))
comb_fn = '%s/%s' % (wdir, cmn.lastName(dn))
for old_fastq in old_fastqs:
cmn.run('cat %s >> %s' % (old_fastq, comb_fn))
log_info.append('%s\t%s\n' % (label, old_fastq))
if hasCombined:
cmn.write_file(''.join(log_info), '%s/combined_libs.log' % wdir)
#make statistics for data amount
fastq_groups = group_fastq(fastqs)
new = []
for key in fastq_groups:
fns = fastq_groups[key]
cmd = 'python /work/biophysics/mtang/SNP_calling/scripts/check_fastq_size.py %s %s' % (
key, ','.join(fns))
new.append(cmd)
new.append('')
cmn.write_lines(new, 'fastq_amount.cmds')
#for tacc, copy fastq to wdir
print('copying fastq for %s...' % olabel)
for fastq in fastqs:
cmd = 'cp %s %s' % (fastq, wdir)
cmn.run(cmd)
fastqs = [cmn.lastName(fastq) for fastq in fastqs]
cmd, fnewSams = make_bwa_cmds(fastqs, 'assembly_selfref_v2', wdir)
info = info.replace('[WL_mapping_cmds]', cmd)
#7. merge mapped sams
cmd = 'python /work/00412/mtang/sequencing/scripts/merge_mapped_sams.py %s_step2.sam %s' % (
olabel, ' '.join(fnewSams))
info = info.replace('[WL_merge_sam_cmds]', cmd)
#8. re-run gatk
#this step has been fully included in the template
fjob = 'job_files/gatk%s.job' % olabel
cmn.write_file(info, fjob)
fjobs.append(fjob)
print(
'##########################################################################'
)
print('please use the following cmd to submit unfinished jobs')
print('cd job_files')
print('\n'.join(['sbatch %s' % cmn.lastName(fjob) for fjob in fjobs]))
print(
'##########################################################################'
)
def get_query_sequence(seqDict, genus, sp):
#1. anything in Eudamine file has higher priority
#fEud = '/project/biophysics/Nick_lab/wli/sequencing/scripts/data/barcodes/Eudaminae-barcode-reference.txt'
#cmd = 'grep %s %s' % (sp, fEud)
#lines = cmn.cmd2lines(cmd)
#if len(lines) == 1:
# name = lines[0].split()[0]
# seq = seqDict[name]
# fasta = '>%s\n%s\n' % (name, seq)
# qlen = len(seq.replace('N', ''))
# print 'pick %s for %s %s' % (name, genus, sp)
# return fasta, qlen
names = list(seqDict.keys())
#try to look up the exact match first
expected_name = '%s_%s' % (genus, sp)
tmp = [name for name in names
if name.upper() == expected_name.upper()]
if len(tmp) != 0:
name = tmp[0]
print('found exact match %s' % name)
seq = seqDict[name]
fasta = '>%s\n%s\n' % (name, seq)
qlen = len(seq.replace('N', ''))
return fasta, qlen
#look it up in other files
good_names = [name for name in names
# if genus.upper() in name.upper().split('_')]
if genus.upper() == name.upper().split('_')[0]]
useGenus = False
if len(good_names) > 0:
useGenus = True
cmn.run('rm pickingLog.txt 2> /dev/null')
if len(good_names) == 0:#sp is just 'sp'
print('can not find barcode for genus keyword "%s"' % genus)
good_names = names
cmn.write_file('noGenus\n', 'pickingLog.txt')
if len(good_names) > 1:
#try to refine it
tmp = [name for name in good_names
if sp.upper() in name.upper().split('_')]
if len(tmp) != 0:
good_names = tmp
else:
cmn.append_file('noSpecies\n', 'pickingLog.txt')
#############################################
####new here, auto pick sequences for those has no info
#############################################
if cmn.filexist('pickingLog.txt'):
print('automatically pick bait by fastq similarity')
fsp = 'restricted_genus.info'
if useGenus and (not cmn.filexist(fsp)):
cmd = '/archive/biophysics/Nick_lab/wli/project/sequencing/scripts/barcode_scripts/auto_rebait.py fqlist %s' % genus
else:
cmd = '/archive/biophysics/Nick_lab/wli/project/sequencing/scripts/barcode_scripts/auto_rebait.py fqlist '
cmn.run(cmd)
good_names = cmn.file2lines('picked_bait.txt')
cmn.write_file('pickClosed\n', 'pickingLog.txt')
#############################################
#############################################
#############################################
#try to see if type species is there
tmp = [name for name in good_names
if name[0] == '*']
if len(tmp) != 0:
good_names = tmp
else:
tmp = [name for name in good_names
if '*' in name]
if len(tmp) != 0:
good_names = tmp
#then randomly pick one, get the max length ones
name = max(good_names, key=lambda x: len(seqDict[x].replace('N', '-')))
#name = name.replace('/', '_')
seq = seqDict[name]
fasta = '>%s\n%s\n' % (name, seq)
qlen = len(seq.replace('N', ''))
print('pick %s for %s %s' % (name, genus, sp))
return fasta, qlen
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#main
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
if __name__=='__main__':
#options=parse_options()
try:
ftree, faln=sys.argv[1:]
except:
print("Usage: *.py ftree fa", file=sys.stderr)
sys.exit()
tree = ete3.Tree(ftree)
takenIDs = []
with open(faln) as fp:
for line in fp:
if line[0] == '>':
ID = line[1:].strip()
takenIDs.append(ID)
tree.prune(takenIDs)
dn = cmn.lastName(ftree).replace('.tre', '') + '_prune.tre'
cmn.write_file(tree.write(), dn)
info = info.replace('[WL_sam_filelist]', dn)
info = info.replace('[WL_preprocessing]', '\n'.join(step1cmds))
#make snp call cmds
#f_sam = merge_sams(sp, fsams)
info = info.replace('5328', sp)
info = info.replace('[WL_cwd]', os.getcwd())
info2 = template2.replace('assembly_selfref', asslabel)
info2 = info2.replace('5328', sp)
info2 = info2.replace('[WL_cwd]', os.getcwd())
os.chdir('..')
fjob = 'job_files/s1_%s.job' % sp
cmn.write_file(info, fjob)
cmn.run('cd job_files; sbatch s1_%s.job' % sp)
if sp not in step1_finished:
step1_jobs.append(fjob)
fjob = 'job_files/s2_%s.job' % sp
cmn.write_file(info2, fjob)
step2_jobs.append(fjob)
#cmn.run('cd job_files; sbatch sg%s.job' % sp)
info = ['bash %s\n' % each for each in step1_jobs]
cmn.write_file(''.join(info), 'step1todo.cmds')
info = ['sbatch %s\n' % each for each in step2_jobs]
except:
print("Usage: *.py RAxML_bestTree.noGap", file=sys.stderr)
sys.exit()
nameDict = get_names()
#t = ete3.Tree(cmn.txt_read(fn).replace('[&U]', ''))
appear = {}
table = []
lines = cmn.file2lines(fn)
info = []
for line in lines:
if line[0] == '>':
sp = line[1:].split('_')[0]
print(sp)
try:
newline = '>' + nameDict[sp].replace('\t', '_').replace(
' ', '_')
except:
newline = line
info.append(newline)
else:
info.append(line)
info.append('')
info = '\n'.join(info)
dn = fn + '.renamed'
cmn.write_file(info, dn)
cmn.write_file(''.join(table), dn + '.nameTable')
seq.append(char2)
else: #different characters
if char1 == '-' and char2 == '-':
seq.append(char3.lower())
elif char1 == '-':
seq.append(char2.lower())
elif char2 == '-':
seq.append(char1.lower())
else:
#different chars and not a gap
seq.append('X')
fasta = '>%s\n%s\n' % (Id, ''.join(seq))
refBaseDict[Id] = ''.join(seq)
new.append(fasta)
cmn.write_file(''.join(new), 'sum_barcodes.fa')
#cmn.run('rm -r sampleRun_fake')
#check denovo pipeline one
fns = cmn.cmd2lines('ls sampleRun_*/denovo_barcode.fa')
denovoDict = {}
new = []
for fn in fns:
Id = cmn.find_between(fn, 'sampleRun_', '/')
lines = cmn.file2lines(fn)
seq = ''.join(lines[1:])
if seq > 658:
tmp = seq.replace('N', '')
if len(tmp) == 658:
seq = tmp
for gene in selected:
scaf, i, j = gene
fa = '../introgression/0_process_scaf/scaf2_fastas/%s.fa' % scaf
seqDict = read_fa(fa)
print('parsing %s (i, j)' % (fa, i, j))
try:
exclusion = repdict[scaf]
except:
exclusion = set([])
for name in seqDict:
#seq = [char for index, char in enumerate(seqDict[name])
# if index not in exclusion and (i <= index <= j)]
seq = seqDict[name][i:j]
seq = [char for index, char in enumerate(seq)
if (index+i) not in exclusion]
try:
final[name] += seq
except:
final[name] = seq
dn = 'sampled_seq_t%s.fa' % times
fasta = ['>%s\n%s\n' % (name, ''.join(final[name]))
for name in final]
cmn.write_file(''.join(fasta), dn)
cov_dict = {}
#get coverage first
for exon in stack_dict:
cov_dict[exon] = {}
for sp in stack_dict[exon]:
stacks = stack_dict[exon][sp]
Nlist = [len(stacks[key]) for key in stacks]
cov = float(sum(Nlist)) / len(Nlist)
cov_dict[exon][sp] = cov
cov_info = [
'%s\t%s\t%s\n' % (sp, exon, cov_dict[exon][sp]) for exon in cov_dict
for sp in cov_dict[exon]
]
cmn.write_file(''.join(cov_info), 'cov_info.txt')
for exon in stack_dict:
length = exon_lengths[exon]
spDict = stack_dict[exon]
for sp in spDict:
stacks = spDict[sp]
newSeq = [[], []]
cov = cov_dict[exon][sp]
for each in range(length):
p = each + 1
print(p, exon, sp)
try:
defline = lines[0]
seq = ''.join(lines[1:])
adict[defline] = seq
return adict
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#main
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
if __name__ == '__main__':
#fn = 'all_genomes_noGap.fa'
#fn = 'all_genomes_charGap.fa'
try:
fn = sys.argv[1]
except:
print('*.py all_genomes_charGap.fa ')
sys.exit()
adict = read_fa(fn)
fnlabel = cmn.lastName(fn).replace('.fa', '')
outdir = 'splitS_%s' % fnlabel
cmn.mkdir(outdir)
for i, key in enumerate(adict):
seq = adict[key]
fasta = '>%s\n%s\n' % (key, seq)
dn = '%s/%s_%s.fa' % (outdir, fnlabel, i)
cmn.write_file(fasta, dn)
#fall = '/project/biophysics/Nick_lab/wli/sequencing/scripts/data/barcodes/all_barcodes.fasta'
seqDict = read_fa(fall)
#fadd = '/project/biophysics/Nick_lab/wli/sequencing/scripts/data/barcodes/addedBaits_fromPipeline.fa'
#if cmn.filexist(fadd):
# seqDict.update(read_fa(fadd))
#ftable = '/archive/biophysics/Nick_lab/wli/archive/barcodes/auto_tables/verified_barcodes.fa'
#seqDict.update(read_autoTable(ftable))
info = []
for line in cmn.file2lines(fn):
#5077 Autochton zarex
items = line.strip().replace('?', ' ').split()
try:
sample, genus, sp = items[:3]
except:
sample, genus = items[:2]
sp = 'sp'
sp = sp.split('-')[0].split('_')[0]
genus = parse_name(genus)
query_sequence, qlen = get_query_sequence(seqDict, genus, sp)
br_result = do_barcode_blast(query_sequence, seqDict)
print('\n'.join(br_result))
baits = pick_barcode_baits(br_result, qlen, seqDict)
info += format_baits(sample, baits)
dn = cmn.lastName(fn) + '.baits'
cmn.write_file(''.join(info), dn)
taken += cmn.cmd2lines(cmd)
taken += [each for each in alea_list
if cmn.lastName(each).split('_')[0] == ID]
if len(words) != 0:
taken = [each for each in taken
if all([word in each for word in words])]
faDict[ID] = taken
#print taken
all_fa = sum(list(faDict.values()), [])
ass_count = count_ass_appearance(all_fa)
best_ass = max(list(ass_count.keys()), key=lambda x: ass_count[x])
print('the most common assembly is %s, only take fa mapped to this assembly' % best_ass)
cmn.write_file(best_ass, 'best_assembly.txt')
sys.exit()
for ID in faDict:
alist = faDict[ID]
taken = [each for each in alist
if best_ass in each.replace('_withMito', '')]
#print ID, taken
if best_ass == 'cne' and len(taken) == 0:
taken += [each for each in alist
if '3574_assembly_v1' in each]
if best_ass == '3574_assembly_v1' and len(taken) == 0:
taken += [each for each in alist
good_reads.append(name1)
elif (misM2 + 1) >= misM1:
#bad one has more mismatch, good one is good!
#good one can be 1 bp more than the bad one
good_reads.append(name1)
else:
if identity >= identity_cut:
good_reads.append(name1)
else:
bad_reads.append((name2, aln1))
print('further classify overlapping reads into:')
print('%s good reads' % len(good_reads))
print('%s bad reads' % len(bad_reads))
#sp2 = name2sp(name2)
#add back the previous IDs
good_reads.append('#' * 100)
for ID in good_IDs:
name = ID1mapping[ID]
good_reads.append(name)
cmn.write_lines(good_reads, 'good_reads.txt')
#bad_reads.append('#' * 100)
for ID in bad_IDs:
name = ID2mapping[ID]
bad_reads.append((name, seqDict2[name]))
bad_alignments = ['%s %s\n' % (each[0], each[1]) for each in bad_reads]
cmn.write_file(''.join(bad_alignments), 'bad_reads_alignment.txt')
print("Usage: *.py fa Ncores", file=sys.stderr)
sys.exit()
#if the nodes are less than 4 taxa, produce a random tree
cmd = "grep '>' %s" % (fn)
lines = [
each[1:].strip() for each in cmn.cmd2lines(cmd) if each.strip() != ''
]
N = len(lines)
if N < 4:
print('Warning: fastme can not make tree of less than 4 taxa')
print('Warning: so I make a fake tree...')
dn = '%s.phylip.fastme.tre' % cmn.lastName(fn)
if N == 1:
info = '(%s);\n' % lines[0]
if N == 2:
a, b = lines
info = '(%s,%s);\n' % (a, b)
elif N == 3:
a, b, c = lines
info = '((%s,%s),%s);\n' % (a, b, c)
cmn.write_file(info, dn)
sys.exit()
label = cmn.lastName(fn)
cmd = 'rm RAxML_*.%s;' % label
cmd += '/home2/wli/local/RAxML/raxmlHPC-PTHREADS-SSE3 -m GTRGAMMA -p 7112 -T %s -s %s -n %s' % (
Ncores, label, label)
cmn.run(cmd)
except:
print('usage: *.py fsam fass', file=sys.stderr)
sys.exit()
cmd = 'module add samtools; samtools faidx %s' % fass
cmn.run(cmd)
cmd = 'module add picard/1.117; java -jar $PICARD/CreateSequenceDictionary.jar R=%s O=%s.dict' % (
fass, fass[:-3])
cmn.run(cmd)
template = cmn.txt_read(
'/project/biophysics/Nick_lab/wli/sequencing/scripts/templates/template_gatk_bias_fromSam.job'
)
template = template.replace('[WL_ref]', fass)
template = template.replace('[INPUT.sam]', fsam)
sampleId = cmn.lastName(fsam).replace('highQ_', '').split('_')[0]
dnlabel = '%s_%s' % (cmn.lastName(fsam).replace(
'.sam', ''), cmn.lastName(fass).replace('.fa', ''))
cmn.mkdir(dnlabel)
os.chdir(dnlabel)
cwd = os.getcwd()
pre_cmds = 'cd %s\n' % cwd
template = template.replace('5642', sampleId)
template = template.replace('[WL_preprossing]', pre_cmds)
cmn.write_file(template, 'gatk%s.job' % sampleId)
#cmn.run('sbatch gatk%s.job' % sampleId)
