def cuffNormUQ(infiles, outfile):
'''Calculate upper quartile (UQ) normalised FPKMs using cuffNorm
'''
# parse the infiles
geneset = infiles[0]
cxb_path = os.path.dirname(infiles[1])
cxb_name = "abundances.cxb"
# Group replicate samples
replicate_field = PARAMS["cufflinks_replicate_field"]
if replicate_field:
if replicate_field not in NAME_FIELD_TITLES:
raise ValueError("cufflinks replicate field not in field titles")
key = [T for T in NAME_FIELD_TITLES if T.lower() != replicate_field]
agg = SAMPLES.groupby(key)
labels = []
cxb_groups = []
for group, indices in agg.groups.iteritems():
labels.append("_".join(group))
group_cxb_files = [
os.path.join(cxb_path, S, cxb_name)
for S in SAMPLES.ix[indices]["sample_id"].values
]
cxb_groups.append(",".join(group_cxb_files))
cxb_files = " ".join(cxb_groups)
else:
sample_ids = SAMPLES["sample_id"].values
cxb_files = " ".join(
[os.path.join(cxb_path, S, cxb_name) for S in sample_ids])
labels = sample_ids
# get the output directory and sample labels
output_dir = os.path.dirname(outfile)
label_str = ",".join(labels)
standards = PARAMS["cufflinks_standards"]
PipelineScRnaseq.runCuffNorm(geneset,
cxb_files,
label_str,
output_dir,
outfile,
library_type=CUFFLINKS_STRAND,
standards_file=standards,
normalisation="quartile",
hits="compatible")
def cuffNormUQ(infiles, outfile):
'''Calculate upper quartile (UQ) normalised FPKMs using cuffNorm
'''
# parse the infiles
geneset = infiles[0]
cxb_path = os.path.dirname(infiles[1])
cxb_name = "abundances.cxb"
# Group replicate samples
replicate_field = PARAMS["cufflinks_replicate_field"]
if replicate_field:
if replicate_field not in NAME_FIELD_TITLES:
raise ValueError("cufflinks replicate field not in field titles")
key = [T for T in NAME_FIELD_TITLES if T.lower() != replicate_field]
agg = SAMPLES.groupby(key)
labels = []
cxb_groups = []
for group, indices in agg.groups.iteritems():
labels.append("_".join(group))
group_cxb_files = [os.path.join(cxb_path, S, cxb_name)
for S in
SAMPLES.ix[indices]["sample_id"].values]
cxb_groups.append(",".join(group_cxb_files))
cxb_files = " ".join(cxb_groups)
else:
sample_ids = SAMPLES["sample_id"].values
cxb_files = " ".join([os.path.join(cxb_path, S, cxb_name)
for S in sample_ids])
labels = sample_ids
# get the output directory and sample labels
output_dir = os.path.dirname(outfile)
label_str = ",".join(labels)
standards = PARAMS["cufflinks_standards"]
PipelineScRnaseq.runCuffNorm(geneset, cxb_files, label_str,
output_dir, outfile,
library_type=CUFFLINKS_STRAND,
standards_file=standards,
normalisation="quartile", hits="compatible")
def cuffNormClassic(infiles, outfile):
'''Calculate classic FPKMs using cuffNorm
for copy number estimation'''
cxb_files = " ".join([f[:-len(".log")] + "/abundances.cxb"
for f in infiles[1:]])
label_str = ",".join([os.path.basename(f)[:-len(".log")]
for f in infiles[1:]])
# parse the infiles
geneset = infiles[0]
# get the output directory and sample labels
output_dir = os.path.dirname(outfile)
PipelineScRnaseq.runCuffNorm(geneset, cxb_files, label_str,
output_dir, outfile,
library_type=CUFFLINKS_STRAND,
normalisation="classic-fpkm", hits="total")
def cuffNormClassic(infiles, outfile):
'''Calculate classic FPKMs using cuffNorm
for copy number estimation'''
cxb_files = " ".join(
[f[:-len(".log")] + "/abundances.cxb" for f in infiles[1:]])
label_str = ",".join(
[os.path.basename(f)[:-len(".log")] for f in infiles[1:]])
# parse the infiles
geneset = infiles[0]
# get the output directory and sample labels
output_dir = os.path.dirname(outfile)
PipelineScRnaseq.runCuffNorm(geneset,
cxb_files,
label_str,
output_dir,
outfile,
library_type=CUFFLINKS_STRAND,
normalisation="classic-fpkm",
hits="total")
