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import unittest
import os
import sys
basedir = os.path.dirname(__file__)
ctrl_rep1 = basedir + "/../src/pytransit/data/glycerol_H37Rv_rep1.wig"
ctrl_rep2 = basedir + "/../src/pytransit/data/glycerol_H37Rv_rep2.wig"
ctrl_data_txt = ",".join([ctrl_rep1, ctrl_rep2])
mini_wig = basedir + "/data/test.wig"
combined_wig = basedir + "/../src/pytransit/data/cholesterol_glycerol_combined.dat"
samples_metadata = basedir + "/../src/pytransit/data/samples_metadata_cg.txt"
samples_metadata_covariates = basedir + "/../src/pytransit/data/samples_metadata_cg_covar.txt"
samples_metadata_interactions = basedir + "/../src/pytransit/data/samples_metadata_cg_interactions.txt"
exp_rep1 = basedir + "/../src/pytransit/data/cholesterol_H37Rv_rep1.wig"
exp_rep2 = basedir + "/../src/pytransit/data/cholesterol_H37Rv_rep2.wig"
exp_rep3 = basedir + "/../src/pytransit/data/cholesterol_H37Rv_rep3.wig"
exp_data_txt = ",".join([exp_rep1, exp_rep2, exp_rep3])
all_data_list = [ctrl_rep1, ctrl_rep2, exp_rep1, exp_rep2, exp_rep3]
annotation = basedir + "/../src/pytransit/genomes/H37Rv.prot_table"
small_annotation = basedir + "/data/test.prot_table"
output = basedir + "/testoutput.txt"
hist_path = output.rsplit(".", 1)[0] + "_histograms"
tpp_output_base = basedir + "/test_tpp_temp"
tpp_output_paths = [tpp_output_base + i for i in [".counts", ".reads1", ".sam", ".tn_stats", ".trimmed1", ".trimmed1_failed_trim", ".wig", "_a.counts", "_b.counts", "_c.counts", "_1.counts", "_2.counts", "_3.counts"]]
# For tpp
reads1 = basedir + "/data/test.fastq"
test_multicontig = basedir + "/data/test-multicontig.fna"
test_multicontig_reads1 = basedir + "/data/test-multicontig-1.fastq"
test_multicontig_reads2 = basedir + "/data/test-multicontig-2.fastq"
h37fna = basedir + "/../src/pytransit/genomes/H37Rv.fna"
class TransitTestCase(unittest.TestCase):
def setUp(self):
# Print header
self.header()
def tearDown(self):
for f in tpp_output_paths:
if os.path.exists(f):
print("Removing tpp test file")
os.remove(f)
if os.path.exists(hist_path):
print("Removing histogram files")
for f in os.listdir(hist_path):
os.remove(os.path.join(hist_path, f))
os.rmdir(hist_path)
# Check if there were output files and remove them
if os.path.exists(output):
print("Removing output file...")
os.remove(output)
genes_path = output.rsplit(".", 1)[0] + "_genes" + output.rsplit(".", 1)[1]
if os.path.exists(genes_path):
print("Removing genes file...")
os.remove(genes_path)
def header(self):
print("\n")
print("#"*20)
print(self.id())
print("#"*20)
def count_hits(path):
hits = 0
for line in open(path):
if line.startswith("#"): continue
tmp = line.split("\t")
if float(tmp[-1]) < 0.05:
hits+=1
return hits
# for ANOVA output; assume last 3 columns are pval, qval, and status
def significant_pvals_qvals(fname, pcol=-2, qcol=-1):
pvals, qvals = [], []
#with open(fname) as f:
# lines = f.readlines()
#for line in lines[2:]:
for line in open(fname):
if line[0]=='#': continue
if "pval" in line and "padj" in line: continue
cols = line.split("\t")
# Read in position as int, and readcounts as float
pvals.append(float(cols[pcol]))
qvals.append(float(cols[qcol]))
return (list(filter(lambda p: p < 0.05, pvals)), list(filter(lambda q: q < 0.05, qvals)))
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