def filterdata(args):
"""
%prog filterdata data.bin samples.ids STR.ids allele_freq remove.ids final.ids
Filter subset of data after dropping remove.ids.
"""
p = OptionParser(filterdata.__doc__)
p.set_cpus()
opts, args = p.parse_args(args)
if len(args) != 6:
sys.exit(not p.print_help())
binfile, sampleids, strids, af, remove, final = args
df, m, samples, loci = read_binfile(binfile, sampleids, strids)
remove = [x.strip() for x in open(remove)]
removes = set(remove)
final = [x.strip() for x in open(final)]
assert len(loci) == len(remove) + len(final)
fp = open(af)
percentiles = {}
for row in fp:
sname, counts = row.split()
countsd = af_to_counts(counts)
percentile = counts_to_percentile(countsd)
percentiles[sname] = percentile
run_args = []
for i, sname in enumerate(loci):
if sname in removes:
continue
a = m[:, i]
percentile = percentiles[sname]
run_args.append((i, a, percentile))
cpus = min(opts.cpus, len(run_args))
p = Pool(processes=cpus)
res = []
for r in p.map_async(convert_to_percentile, run_args).get():
res.append(r)
res.sort()
# Write mask (P-value) matrix
ii, pvalues = zip(*res)
m = np.vstack(pvalues).T
write_csv("final.mask.tsv", m, samples, final)
df.drop(remove, inplace=True, axis=1)
df.columns = final
# Save a copy of the raw numpy array
filtered_bin = "filtered.bin"
m = df.as_matrix()
m[m < 0] = -1
m.tofile(filtered_bin)
logging.debug("Binary matrix written to `{}`".format(filtered_bin))
# Write data output
df.to_csv("final.data.tsv", sep="\t", index_label="SampleKey")
def filterdata(args):
"""
%prog filterdata data.bin samples.ids STR.ids allele_freq remove.ids final.ids
Filter subset of data after dropping remove.ids.
"""
p = OptionParser(filterdata.__doc__)
p.set_cpus()
opts, args = p.parse_args(args)
if len(args) != 6:
sys.exit(not p.print_help())
binfile, sampleids, strids, af, remove, final = args
df, m, samples, loci = read_binfile(binfile, sampleids, strids)
remove = [x.strip() for x in open(remove)]
removes = set(remove)
final = [x.strip() for x in open(final)]
assert len(loci) == len(remove) + len(final)
fp = open(af)
percentiles = {}
for row in fp:
sname, counts = row.split()
countsd = af_to_counts(counts)
percentile = counts_to_percentile(countsd)
percentiles[sname] = percentile
run_args = []
for i, sname in enumerate(loci):
if sname in removes:
continue
a = m[:, i]
percentile = percentiles[sname]
run_args.append((i, a, percentile))
cpus = min(opts.cpus, len(run_args))
p = Pool(processes=cpus)
res = []
for r in p.map_async(convert_to_percentile, run_args).get():
res.append(r)
res.sort()
# Write mask (P-value) matrix
ii, pvalues = zip(*res)
m = np.vstack(pvalues).T
write_csv("final.mask.tsv", m, samples, final)
df.drop(remove, inplace=True, axis=1)
df.columns = final
# Save a copy of the raw numpy array
filtered_bin = "filtered.bin"
m = df.as_matrix()
m[m < 0] = -1
m.tofile(filtered_bin)
logging.debug("Binary matrix written to `{}`".format(filtered_bin))
# Write data output
df.to_csv("final.data.tsv", sep="\t", index_label="SampleKey")
def write_mask(cpus, samples, final_columns, run_args, filename="mask.tsv"):
p = Pool(processes=cpus)
res = []
r = p.map_async(convert_to_percentile, run_args, callback=res.append)
r.wait()
res.sort()
if len(res) == 1: # sometimes res end up with one more nest
res, = res
# Write mask (P-value) matrix
ii, pvalues = zip(*res)
m = np.vstack(pvalues).T
write_csv(filename, m, samples, final_columns)
def write_mask(cpus, samples, final_columns, run_args, filename="mask.tsv"):
p = Pool(processes=cpus)
res = []
r = p.map_async(convert_to_percentile, run_args,
callback=res.append)
r.wait()
res.sort()
if len(res) == 1: # sometimes res end up with one more nest
res, = res
# Write mask (P-value) matrix
ii, pvalues = zip(*res)
m = np.vstack(pvalues).T
write_csv(filename, m, samples, final_columns)
def count(args):
"""
%prog count *.gz
Count reads based on FASTQC results. FASTQC needs to be run on all the input
data given before running this command.
"""
from jcvi.utils.table import loadtable, write_csv
p = OptionParser(count.__doc__)
p.add_option("--dir",
help="Sub-directory where FASTQC was run [default: %default]")
p.add_option("--human",
default=False,
action="store_true",
help="Human friendly numbers [default: %default]")
p.set_table()
p.set_outfile()
opts, args = p.parse_args(args)
if len(args) < 1:
sys.exit(not p.print_help())
filenames = args
subdir = opts.dir
header = "Filename|Total Sequences|Sequence length|Total Bases".split("|")
rows = []
human = opts.human
for f in filenames:
folder = f.replace(".gz", "").rsplit(".", 1)[0] + "_fastqc"
if subdir:
folder = op.join(subdir, folder)
summaryfile = op.join(folder, "fastqc_data.txt")
fqcdata = FastQCdata(summaryfile, human=human)
row = [fqcdata[x] for x in header]
rows.append(row)
print >> sys.stderr, loadtable(header, rows)
write_csv(header,
rows,
sep=opts.sep,
filename=opts.outfile,
align=opts.align)
def __init__(self, filename, delimiter=','):
super(Layout, self).__init__(filename)
if not op.exists(filename):
ksfiles = iglob(".", "*.ks")
header = "Ks file|ncomponents|label|color|marker".split("|")
contents = []
for ksfile in ksfiles:
leg = op.basename(ksfile).rsplit(".", 1)[0]
if leg.count(".") == 1:
leg = leg.replace(".", " *vs.* ")
contents.append((ksfile, "1", leg, "", ""))
write_csv(header, contents, comment=True, filename=filename)
fp = open(filename)
for row in fp:
if row[0] == '#':
continue
self.append(LayoutLine(row, delimiter=delimiter))
self.assign_colors()
self.assign_markers()
def __init__(self, filename, delimiter=','):
super(Layout, self).__init__(filename)
if not op.exists(filename):
ksfiles = iglob(".", "*.ks")
header = "Ks file|ncomponents|label|color|marker".split("|")
contents = []
for ksfile in ksfiles:
leg = op.basename(ksfile).rsplit(".", 1)[0]
if leg.count(".") == 1:
leg = leg.replace(".", " *vs.* ")
contents.append((ksfile, "1", leg, "", ""))
write_csv(header, contents, comment=True, filename=filename)
fp = open(filename)
for row in fp:
if row[0] == '#':
continue
self.append(LayoutLine(row, delimiter=delimiter))
self.assign_colors()
self.assign_markers()
def count(args):
"""
%prog count *.gz
Count reads based on FASTQC results. FASTQC needs to be run on all the input
data given before running this command.
"""
from jcvi.utils.table import loadtable, write_csv
p = OptionParser(count.__doc__)
p.add_option("--dir",
help="Sub-directory where FASTQC was run [default: %default]")
p.add_option("--human", default=False, action="store_true",
help="Human friendly numbers [default: %default]")
p.set_table()
p.set_outfile()
opts, args = p.parse_args(args)
if len(args) < 1:
sys.exit(not p.print_help())
filenames = args
subdir = opts.dir
header = "Filename|Total Sequences|Sequence length|Total Bases".split("|")
rows = []
human = opts.human
for f in filenames:
folder = f.replace(".gz", "").rsplit(".", 1)[0] + "_fastqc"
if subdir:
folder = op.join(subdir, folder)
summaryfile = op.join(folder, "fastqc_data.txt")
fqcdata = FastQCdata(summaryfile, human=human)
row = [fqcdata[x] for x in header]
rows.append(row)
print >> sys.stderr, loadtable(header, rows)
write_csv(header, rows, sep=opts.sep,
filename=opts.outfile, align=opts.align)
def summary(args):
"""
%prog summary agpfile
print a table of scaffold statistics, number of BACs, no of scaffolds,
scaffold N50, scaffold L50, actual sequence, PSMOL NNNs, PSMOL-length, % of
PSMOL sequenced.
"""
from jcvi.utils.table import write_csv
p = OptionParser(summary.__doc__)
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(p.print_help())
agpfile, = args
header = "Chromosome #_Distinct #_Components #_Scaffolds " \
"Scaff_N50 Scaff_L50 Length".split()
agp = AGP(agpfile)
data = list(agp.summary_all())
write_csv(header, data, sep=" ")
def summary(args):
"""
%prog summary agpfile
print a table of scaffold statistics, number of BACs, no of scaffolds,
scaffold N50, scaffold L50, actual sequence, PSMOL NNNs, PSMOL-length, % of
PSMOL sequenced.
"""
from jcvi.utils.table import write_csv
p = OptionParser(summary.__doc__)
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(p.print_help())
agpfile, = args
header = "Chromosome #_Distinct #_Components #_Scaffolds " \
"Scaff_N50 Scaff_L50 Length".split()
agp = AGP(agpfile)
data = list(agp.summary_all())
write_csv(header, data, sep=" ")
def stats(args):
"""
%prog stats folder
Generate table summarizing .stats files.
"""
p = OptionParser(stats.__doc__)
p.set_outfile()
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
folder, = args
statsfiles = iglob(folder, "*.stats")
after_equal = lambda x: x.split("=")[-1]
header = "Library Assembled_reads Contigs".split()
contents = []
# label=M0096 total=7443 cnts=948 mean=7.851 std=35.96
for statsfile in statsfiles:
fp = open(statsfile)
for row in fp:
if row.startswith("label="):
break
label, total, cnts = row.split()[:3]
label = after_equal(label)
reads = int(after_equal(total))
contigs = int(after_equal(cnts))
contents.append((label, reads, contigs))
all_labels, all_reads, all_contigs = zip(*contents)
contents.append(("SUM", sum(all_reads), sum(all_contigs)))
contents.append(("AVERAGE (per sample)", \
int(np.mean(all_reads)), int(np.mean(all_contigs))))
contents.append(("MEDIAN (per sample)", \
int(np.median(all_reads)), int(np.median(all_contigs))))
write_csv(header, contents, filename=opts.outfile)
def ystr(args):
"""
%prog ystr chrY.vcf
Print out Y-STR info given VCF. Marker name extracted from tabfile.
"""
from jcvi.utils.table import write_csv
p = OptionParser(ystr.__doc__)
p.set_home("lobstr")
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
vcffile, = args
si = STRFile(opts.lobstr_home, db="hg38-named")
register = si.register
header = "Marker|Reads|Ref|Genotype|Motif".split("|")
contents = []
fp = must_open(vcffile)
reader = vcf.Reader(fp)
simple_register = {}
for record in reader:
name = register[(record.CHROM, record.POS)]
info = record.INFO
ref = int(float(info["REF"]))
rpa = info.get("RPA", ref)
if isinstance(rpa, list):
rpa = "|".join(str(int(float(x))) for x in rpa)
ru = info["RU"]
simple_register[name] = rpa
for sample in record.samples:
contents.append((name, sample["ALLREADS"], ref, rpa, ru))
# Multi-part markers
a, b, c = "DYS389I", "DYS389B.1", "DYS389B"
if a in simple_register and b in simple_register:
simple_register[c] = int(simple_register[a]) + int(simple_register[b])
# Multi-copy markers
mm = ["DYS385", "DYS413", "YCAII"]
for m in mm:
ma, mb = m + 'a', m + 'b'
if ma not in simple_register or mb not in simple_register:
simple_register[ma] = simple_register[mb] = None
del simple_register[ma]
del simple_register[mb]
continue
if simple_register[ma] > simple_register[mb]:
simple_register[ma], simple_register[mb] = \
simple_register[mb], simple_register[ma]
write_csv(header, contents, sep=" ")
print("[YSEARCH]")
build_ysearch_link(simple_register)
print("[YFILER]")
build_yhrd_link(simple_register, panel=YHRD_YFILER)
print("[YFILERPLUS]")
build_yhrd_link(simple_register, panel=YHRD_YFILERPLUS)
print("[YSTR-ALL]")
build_yhrd_link(simple_register, panel=USYSTR_ALL)
def prepare(args):
"""
%prog prepare "B. oleracea" *.fastq
Scan input fastq files (see below) and create `in_groups.csv` and
`in_libs.csv`. The species name does not really matter.
"""
from jcvi.utils.table import write_csv
from jcvi.formats.base import write_file
from jcvi.formats.fastq import guessoffset
p = OptionParser(prepare.__doc__ + FastqNamings)
p.add_option("--corr", default=False, action="store_true",
help="Extra parameters for corrected data [default: %default]")
p.add_option("--norun", default=False, action="store_true",
help="Don't write `run.sh` script [default: %default]")
p.add_option("--ploidy", default="2", choices=("1", "2"),
help="Ploidy [default: %default]")
p.set_cpus()
opts, args = p.parse_args(args)
if len(args) < 1:
sys.exit(not p.print_help())
organism_name = args[0]
project_name = "".join(x[0] for x in organism_name.split()).upper()
fnames = sorted(glob("*.fastq*") if len(args) == 1 else args[1:])
for x in fnames:
assert op.exists(x), "File `{0}` not found.".format(x)
offset = guessoffset([fnames[0]])
phred64 = offset == 64
assert all(guessoffset([x]) == offset for x in fnames[1:])
groupheader = "group_name library_name file_name".split()
libheader = "library_name project_name organism_name type paired "\
"frag_size frag_stddev insert_size insert_stddev read_orientation "\
"genomic_start genomic_end".split()
groupcontents = []
libs = []
for file_name in fnames:
group_name = op.basename(file_name).split(".")[0]
library_name = "-".join(group_name.split("-")[:2])
# Handle paired files and convert to wildcard
if ".1." in file_name:
file_name = file_name.replace(".1.", ".?.")
elif ".2." in file_name:
continue
groupcontents.append((group_name, library_name, file_name))
if library_name not in libs:
libs.append(library_name)
libcontents = []
for library_name in libs:
L = Library(library_name)
size = L.size
stddev = L.stddev
type = L.type
paired = L.paired
read_orientation = L.read_orientation
size = size or ""
stddev = stddev or ""
frag_size = size if type == "fragment" else ""
frag_stddev = stddev if type == "fragment" else ""
insert_size = size if type != "fragment" else ""
insert_stddev = stddev if type != "fragment" else ""
genomic_start, genomic_end = "", ""
libcontents.append((library_name, project_name, organism_name, type, \
paired, frag_size, frag_stddev, insert_size, insert_stddev, \
read_orientation, genomic_start, genomic_end))
write_csv(groupheader, groupcontents, filename="in_groups.csv", tee=True)
logging.debug("`in_group.csv` created (# of groups = {0}).".\
format(len(groupcontents)))
write_csv(libheader, libcontents, filename="in_libs.csv", tee=True)
logging.debug("`in_libs.csv` created (# of libs = {0}).".\
format(len(libcontents)))
runfile = "run.sh"
extra = ""
if opts.corr:
extra += "FE_NUM_CYCLES=1 EC_K=28 FE_QUAL_CEIL_RADIUS=0"
extra += " REMOVE_DODGY_READS_FRAG=False FE_MAX_KMER_FREQ_TO_MARK=1"
if not opts.norun:
contents = ALLPATHSRUN.format(opts.ploidy, opts.cpus, phred64, extra)
write_file(runfile, contents)
def plot(args):
"""
%prog plot tagged.new.bed chr1
Plot gene identifiers along a particular chromosome, often to illustrate the
gene id assignment procedure.
"""
from jcvi.graphics.base import plt, savefig
from jcvi.graphics.chromosome import ChromosomeMap
p = OptionParser(plot.__doc__)
p.add_option("--firstn", type="int", help="Only plot the first N genes")
p.add_option("--ymax", type="int", help="Y-axis max value")
p.add_option("--log",
action="store_true",
help="Write plotting data [default: %default]")
opts, args, iopts = p.set_image_options(args, figsize="6x4")
if len(args) != 2:
sys.exit(not p.print_help())
taggedbed, chr = args
bed = Bed(taggedbed)
beds = list(bed.sub_bed(chr))
old, new = [], []
i = 0
for b in beds:
accn = b.extra[0]
if "te" in accn:
continue
accn, tag = accn.split("|")
if tag == "OVERLAP":
continue
c, r = atg_name(accn)
if tag == "NEW":
new.append((i, r))
else:
old.append((i, r))
i += 1
ngenes = i
assert ngenes == len(new) + len(old)
logging.debug("Imported {0} ranks on {1}.".format(ngenes, chr))
fig = plt.figure(1, (iopts.w, iopts.h))
root = fig.add_axes([0, 0, 1, 1])
xstart, xend = .2, .8
ystart, yend = .2, .8
pad = .02
ngenes = opts.firstn or ngenes
ymax = opts.ymax or 500000
title = "Assignment of Medtr identifiers"
if opts.ymax:
subtitle = "{0}, first {1} genes".format(chr, ngenes)
else:
subtitle = "{0}, {1} genes ({2} new)".format(chr, ngenes, len(new))
chr_map = ChromosomeMap(fig, root, xstart, xend, ystart, yend, pad, 0,
ymax, 5, title, subtitle)
ax = chr_map.axes
if opts.log:
from jcvi.utils.table import write_csv
header = ["x", "y"]
write_csv(header, new, filename=chr + ".new")
write_csv(header, old, filename=chr + ".old")
x, y = zip(*new)
ax.plot(x, y, "b,")
x, y = zip(*old)
ax.plot(x, y, "r,")
# Legends
ymid = (ystart + yend) / 2
y = ymid + pad
root.plot([.2], [y], "r.", lw=2)
root.text(.2 + pad, y, "Existing Medtr ids", va="center", size=10)
y = ymid - pad
root.plot([.2], [y], "b.", lw=2)
root.text(.2 + pad, y, "Newly instantiated ids", va="center", size=10)
ax.set_xlim(0, ngenes)
ax.set_ylim(0, ymax)
ax.set_axis_off()
root.set_xlim(0, 1)
root.set_ylim(0, 1)
root.set_axis_off()
image_name = chr + ".identifiers." + iopts.format
savefig(image_name, dpi=iopts.dpi, iopts=iopts)
def ystr(args):
"""
%prog ystr chrY.vcf
Print out Y-STR info given VCF. Marker name extracted from tabfile.
"""
from jcvi.utils.table import write_csv
p = OptionParser(ystr.__doc__)
p.set_home("lobstr")
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
vcffile, = args
si = STRFile(opts.lobstr_home, db="hg38-named")
register = si.register
header = "Marker|Reads|Ref|Genotype|Motif".split("|")
contents = []
fp = must_open(vcffile)
reader = vcf.Reader(fp)
simple_register = {}
for record in reader:
name = register[(record.CHROM, record.POS)]
info = record.INFO
ref = int(float(info["REF"]))
rpa = info.get("RPA", ref)
if isinstance(rpa, list):
rpa = "|".join(str(int(float(x))) for x in rpa)
ru = info["RU"]
simple_register[name] = rpa
for sample in record.samples:
contents.append((name, sample["ALLREADS"], ref, rpa, ru))
# Multi-part markers
a, b, c = "DYS389I", "DYS389B.1", "DYS389B"
if a in simple_register and b in simple_register:
simple_register[c] = int(simple_register[a]) + int(simple_register[b])
# Multi-copy markers
mm = ["DYS385", "DYS413", "YCAII"]
for m in mm:
ma, mb = m + 'a', m + 'b'
if ma not in simple_register or mb not in simple_register:
simple_register[ma] = simple_register[mb] = None
del simple_register[ma]
del simple_register[mb]
continue
if simple_register[ma] > simple_register[mb]:
simple_register[ma], simple_register[mb] = \
simple_register[mb], simple_register[ma]
write_csv(header, contents, sep=" ")
print "[YSEARCH]"
build_ysearch_link(simple_register)
print "[YFILER]"
build_yhrd_link(simple_register, panel=YHRD_YFILER)
print "[YFILERPLUS]"
build_yhrd_link(simple_register, panel=YHRD_YFILERPLUS)
print "[YSTR-ALL]"
build_yhrd_link(simple_register, panel=USYSTR_ALL)
def plot(args):
"""
%prog plot tagged.new.bed chr1
Plot gene identifiers along a particular chromosome, often to illustrate the
gene id assignment procedure.
"""
from jcvi.graphics.base import plt, savefig
from jcvi.graphics.chromosome import ChromosomeMap
p = OptionParser(plot.__doc__)
p.add_option("--firstn", type="int", help="Only plot the first N genes")
p.add_option("--ymax", type="int", help="Y-axis max value")
p.add_option("--log", action="store_true",
help="Write plotting data [default: %default]")
opts, args, iopts = p.set_image_options(args, figsize="6x4")
if len(args) != 2:
sys.exit(not p.print_help())
taggedbed, chr = args
bed = Bed(taggedbed)
beds = list(bed.sub_bed(chr))
old, new = [], []
i = 0
for b in beds:
accn = b.extra[0]
if "te" in accn:
continue
accn, tag = accn.split("|")
if tag == "OVERLAP":
continue
c, r = atg_name(accn)
if tag == "NEW":
new.append((i, r))
else:
old.append((i, r))
i += 1
ngenes = i
assert ngenes == len(new) + len(old)
logging.debug("Imported {0} ranks on {1}.".format(ngenes, chr))
fig = plt.figure(1, (iopts.w, iopts.h))
root = fig.add_axes([0, 0, 1, 1])
xstart, xend = .2, .8
ystart, yend = .2, .8
pad = .02
ngenes = opts.firstn or ngenes
ymax = opts.ymax or 500000
title = "Assignment of Medtr identifiers"
if opts.ymax:
subtitle = "{0}, first {1} genes".format(chr, ngenes)
else:
subtitle = "{0}, {1} genes ({2} new)".format(chr, ngenes, len(new))
chr_map = ChromosomeMap(fig, root, xstart, xend, ystart, yend, pad, 0,
ymax, 5, title, subtitle)
ax = chr_map.axes
if opts.log:
from jcvi.utils.table import write_csv
header = ["x", "y"]
write_csv(header, new, filename=chr + ".new")
write_csv(header, old, filename=chr + ".old")
x, y = zip(*new)
ax.plot(x, y, "b,")
x, y = zip(*old)
ax.plot(x, y, "r,")
# Legends
ymid = (ystart + yend) / 2
y = ymid + pad
root.plot([.2], [y], "r.", lw=2)
root.text(.2 + pad, y, "Existing Medtr ids", va="center", size=10)
y = ymid - pad
root.plot([.2], [y], "b.", lw=2)
root.text(.2 + pad, y, "Newly instantiated ids", va="center", size=10)
ax.set_xlim(0, ngenes)
ax.set_ylim(0, ymax)
ax.set_axis_off()
root.set_xlim(0, 1)
root.set_ylim(0, 1)
root.set_axis_off()
image_name = chr + ".identifiers." + iopts.format
savefig(image_name, dpi=iopts.dpi, iopts=iopts)
def prepare(args):
"""
%prog prepare "B. oleracea" *.fastq
Scan input fastq files (see below) and create `in_groups.csv` and
`in_libs.csv`. The species name does not really matter.
"""
from jcvi.utils.table import write_csv
from jcvi.formats.base import check_exists
p = OptionParser(prepare.__doc__ + FastqNamings)
p.add_option("--norun", default=False, action="store_true",
help="Don't write `run.sh` script [default: %default]")
opts, args = p.parse_args(args)
if len(args) < 1:
sys.exit(not p.print_help())
organism_name = args[0]
project_name = "".join(x[0] for x in organism_name.split()).upper()
fnames = sorted(glob("*.fastq*") if len(args) == 1 else args[1:])
for x in fnames:
assert op.exists(x), "File `{0}` not found.".format(x)
groupheader = "group_name library_name file_name".split()
libheader = "library_name project_name organism_name type paired "\
"frag_size frag_stddev insert_size insert_stddev read_orientation "\
"genomic_start genomic_end".split()
groupcontents = []
libs = []
for file_name in fnames:
group_name = op.basename(file_name).split(".")[0]
library_name = "-".join(group_name.split("-")[:2])
# Handle paired files and convert to wildcard
if ".1." in file_name:
file_name = file_name.replace(".1.", ".?.")
elif ".2." in file_name:
continue
groupcontents.append((group_name, library_name, file_name))
if library_name not in libs:
libs.append(library_name)
libcontents = []
for library_name in libs:
L = Library(library_name)
size = L.size
stddev = L.stddev
type = L.type
paired = L.paired
read_orientation = L.read_orientation
size = size or ""
stddev = stddev or ""
frag_size = size if type == "fragment" else ""
frag_stddev = stddev if type == "fragment" else ""
insert_size = size if type != "fragment" else ""
insert_stddev = stddev if type != "fragment" else ""
genomic_start, genomic_end = "", ""
libcontents.append((library_name, project_name, organism_name, type, \
paired, frag_size, frag_stddev, insert_size, insert_stddev, \
read_orientation, genomic_start, genomic_end))
write_csv(groupheader, groupcontents, filename="in_groups.csv", tee=True)
logging.debug("`in_group.csv` created (# of groups = {0}).".\
format(len(groupcontents)))
write_csv(libheader, libcontents, filename="in_libs.csv", tee=True)
logging.debug("`in_libs.csv` created (# of libs = {0}).".\
format(len(libcontents)))
runfile = "run.sh"
if not opts.norun and check_exists(runfile):
fw = open(runfile, "w")
print >> fw, ALLPATHSRUN
logging.debug("Run script written to `{0}`.".format(runfile))
def prepare(args):
"""
%prog prepare "B. oleracea" *.fastq
Scan input fastq files (see below) and create `in_groups.csv` and
`in_libs.csv`. The species name does not really matter.
"""
from jcvi.utils.table import write_csv
from jcvi.formats.base import check_exists
p = OptionParser(prepare.__doc__ + FastqNamings)
p.add_option("--norun", default=False, action="store_true",
help="Don't write `run.sh` script [default: %default]")
opts, args = p.parse_args(args)
if len(args) < 1:
sys.exit(not p.print_help())
organism_name = args[0]
project_name = "".join(x[0] for x in organism_name.split()).upper()
fnames = sorted(glob("*.fastq*") if len(args) == 1 else args[1:])
for x in fnames:
assert op.exists(x), "File `{0}` not found.".format(x)
groupheader = "group_name library_name file_name".split()
libheader = "library_name project_name organism_name type paired "\
"frag_size frag_stddev insert_size insert_stddev read_orientation "\
"genomic_start genomic_end".split()
groupcontents = []
libs = []
for file_name in fnames:
group_name = op.basename(file_name).split(".")[0]
library_name = "-".join(group_name.split("-")[:2])
# Handle paired files and convert to wildcard
if ".1." in file_name:
file_name = file_name.replace(".1.", ".?.")
elif ".2." in file_name:
continue
groupcontents.append((group_name, library_name, file_name))
if library_name not in libs:
libs.append(library_name)
libcontents = []
for library_name in libs:
L = Library(library_name)
size = L.size
stddev = L.stddev
type = L.type
paired = L.paired
read_orientation = L.read_orientation
size = size or ""
stddev = stddev or ""
frag_size = size if type == "fragment" else ""
frag_stddev = stddev if type == "fragment" else ""
insert_size = size if type != "fragment" else ""
insert_stddev = stddev if type != "fragment" else ""
genomic_start, genomic_end = "", ""
libcontents.append((library_name, project_name, organism_name, type, \
paired, frag_size, frag_stddev, insert_size, insert_stddev, \
read_orientation, genomic_start, genomic_end))
write_csv(groupheader, groupcontents, filename="in_groups.csv", tee=True)
logging.debug("`in_group.csv` created (# of groups = {0}).".\
format(len(groupcontents)))
write_csv(libheader, libcontents, filename="in_libs.csv", tee=True)
logging.debug("`in_libs.csv` created (# of libs = {0}).".\
format(len(libcontents)))
runfile = "run.sh"
if not opts.norun and check_exists(runfile):
fw = open(runfile, "w")
print >> fw, ALLPATHSRUN
logging.debug("Run script written to `{0}`.".format(runfile))
