def _detect_rRNA(data):
gtf_file = dd.get_gtf_file(data)
count_file = dd.get_count_file(data)
rrna_features = gtf.get_rRNA(gtf_file)
genes = [x[0] for x in rrna_features if x]
count_table = pd.read_csv(count_file, sep="\t", names=["id", "counts"])
return {'rRNA': sum(count_table.ix[genes]["counts"])}
def _detect_rRNA(data, out_dir):
out_file = os.path.join(out_dir, "rRNA_metrics.txt")
if not utils.file_exists(out_file):
gtf_file = dd.get_gtf_file(data)
quant = tz.get_in(["quant", "tsv"], data)
if not quant:
salmon_dir = dd.get_salmon_dir(data)
if salmon_dir:
quant = os.path.join(salmon_dir, "quant.sf")
logger.info("Calculating RNA-seq rRNA metrics for %s." % quant)
rrna_features = gtf.get_rRNA(gtf_file)
transcripts = set([x[1] for x in rrna_features if x])
if not (transcripts and quant and utils.file_exists(quant)):
return {'rRNA': "NA", "rRNA_rate": "NA"}
sample_table = pd.read_csv(quant, sep="\t")
rrna_exp = list(
map(
float, sample_table[sample_table["Name"].isin(transcripts)]
["NumReads"]))
total_exp = list(map(float, sample_table["NumReads"]))
rrna = sum(rrna_exp)
if sum(total_exp) == 0:
rrna_rate = "NA"
else:
rrna_rate = float(rrna) / sum(total_exp)
with file_transaction(out_file) as tx_out_file:
with open(tx_out_file, "w") as out_handle:
out_handle.write(",".join(["rRNA", str(rrna)]) + "\n")
out_handle.write(
",".join(["rRNA_rate", str(rrna_rate)]) + "\n")
return _read_memoized_rrna(out_file)
def _find_rRNA_genes(gtf_file, rrna_file):
print(gtf_file)
rrna_features = gtf.get_rRNA(gtf_file)
transcripts = set([x[0] for x in rrna_features if x])
with open(rrna_file, 'w') as outh:
outh.write("\n".join(transcripts))
return rrna_file
def _detect_rRNA(data):
gtf_file = dd.get_gtf_file(data)
count_file = dd.get_count_file(data)
rrna_features = gtf.get_rRNA(gtf_file)
genes = [x[0] for x in rrna_features if x]
count_table = pd.read_csv(count_file, sep="\t", names=["id", "counts"])
return {'rRNA': sum(count_table.ix[genes]["counts"])}
def _find_rRNA_genes(gtf_file, rrna_file):
print(gtf_file)
rrna_features = gtf.get_rRNA(gtf_file)
transcripts = set([x[0] for x in rrna_features if x])
with open(rrna_file, 'w') as outh:
outh.write("\n".join(transcripts))
return rrna_file
def _detect_rRNA(data, out_dir):
out_file = os.path.join(out_dir, "rRNA_metrics.txt")
if not utils.file_exists(out_file):
gtf_file = dd.get_gtf_file(data)
quant = tz.get_in(["quant", "tsv"], data)
if not quant:
salmon_dir = dd.get_salmon_dir(data)
if salmon_dir:
quant = os.path.join(salmon_dir, "quant", "quant.sf")
logger.info("Calculating RNA-seq rRNA metrics for %s." % quant)
rrna_features = gtf.get_rRNA(gtf_file)
transcripts = set([x[1] for x in rrna_features if x])
if not (transcripts and quant and utils.file_exists(quant)):
return {'rRNA': "NA", "rRNA_rate": "NA"}
sample_table = pd.read_csv(quant, sep="\t")
rrna_exp = list(map(float, sample_table[sample_table["Name"].isin(transcripts)]["NumReads"]))
total_exp = list(map(float, sample_table["NumReads"]))
rrna = sum(rrna_exp)
if sum(total_exp) == 0:
rrna_rate = "NA"
else:
rrna_rate = float(rrna) / sum(total_exp)
with file_transaction(out_file) as tx_out_file:
with open(tx_out_file, "w") as out_handle:
out_handle.write(",".join(["rRNA", str(rrna)]) + "\n")
out_handle.write(",".join(["rRNA_rate", str(rrna_rate)]) + "\n")
return _read_memoized_rrna(out_file)
def _detect_rRNA(data):
gtf_file = dd.get_gtf_file(data)
count_file = dd.get_count_file(data)
rrna_features = gtf.get_rRNA(gtf_file)
genes = [x[0] for x in rrna_features if x]
if not genes:
return {'rRNA': "NA", "rRNA_rate": "NA"}
count_table = pd.read_csv(count_file, sep="\t", names=["id", "counts"])
rrna = sum(count_table[count_table["id"].isin(genes)]["counts"])
rrna_rate = float(rrna) / sum(count_table["counts"])
return {'rRNA': str(rrna), 'rRNA_rate': str(rrna_rate)}
def _detect_rRNA(data):
sample = dd.get_sample_name(data)
gtf_file = dd.get_gtf_file(data)
tidy_file = dd.get_sailfish_tidy(data)
rrna_features = gtf.get_rRNA(gtf_file)
transcripts = set([x[1] for x in rrna_features if x])
if not transcripts:
return {'rRNA': "NA", "rRNA_rate": "NA"}
count_table = pd.read_csv(tidy_file, sep="\t")
sample_table = count_table[count_table["sample"].isin([sample])]
rrna_exp = map(float, sample_table[sample_table["id"].isin(transcripts)]["numreads"])
total_exp = map(float, sample_table["numreads"])
rrna = sum(rrna_exp)
rrna_rate = float(rrna) / sum(total_exp)
return {'rRNA': str(rrna), 'rRNA_rate': str(rrna_rate)}
def _detect_rRNA(data):
sample = dd.get_sample_name(data)
gtf_file = dd.get_gtf_file(data)
tidy_file = dd.get_sailfish_tidy(data)
rrna_features = gtf.get_rRNA(gtf_file)
transcripts = set([x[1] for x in rrna_features if x])
if not transcripts:
return {'rRNA': "NA", "rRNA_rate": "NA"}
count_table = pd.read_csv(tidy_file, sep="\t")
sample_table = count_table[count_table["sample"].isin([sample])]
rrna_exp = map(
float, sample_table[sample_table["id"].isin(transcripts)]["numreads"])
total_exp = map(float, sample_table["numreads"])
rrna = sum(rrna_exp)
rrna_rate = float(rrna) / sum(total_exp)
return {'rRNA': str(rrna), 'rRNA_rate': str(rrna_rate)}
def _detect_rRNA(data):
sample = dd.get_sample_name(data)
gtf_file = dd.get_gtf_file(data)
sailfish_dir = dd.get_sailfish_dir(data)
quant = os.path.join(sailfish_dir, "quant", "quant.sf")
rrna_features = gtf.get_rRNA(gtf_file)
transcripts = set([x[1] for x in rrna_features if x])
if not (transcripts and utils.file_exists(quant)):
return {'rRNA': "NA", "rRNA_rate": "NA"}
sample_table = pd.read_csv(quant, sep="\t")
rrna_exp = map(float, sample_table[sample_table["Name"].isin(transcripts)]["NumReads"])
total_exp = map(float, sample_table["NumReads"])
rrna = sum(rrna_exp)
if sum(total_exp) == 0:
return {'rRNA': str(rrna), 'rRNA_rate': "NA"}
rrna_rate = float(rrna) / sum(total_exp)
return {'rRNA': str(rrna), 'rRNA_rate': str(rrna_rate)}
def _detect_rRNA(data):
sample = dd.get_sample_name(data)
gtf_file = dd.get_gtf_file(data)
salmon_dir = dd.get_salmon_dir(data)
quant = os.path.join(salmon_dir, "quant", "quant.sf")
rrna_features = gtf.get_rRNA(gtf_file)
transcripts = set([x[1] for x in rrna_features if x])
if not (transcripts and utils.file_exists(quant)):
return {'rRNA': "NA", "rRNA_rate": "NA"}
sample_table = pd.read_csv(quant, sep="\t")
rrna_exp = map(
float,
sample_table[sample_table["Name"].isin(transcripts)]["NumReads"])
total_exp = map(float, sample_table["NumReads"])
rrna = sum(rrna_exp)
if sum(total_exp) == 0:
return {'rRNA': str(rrna), 'rRNA_rate': "NA"}
rrna_rate = float(rrna) / sum(total_exp)
return {'rRNA': str(rrna), 'rRNA_rate': str(rrna_rate)}