(_,
input_path,
output_path,
+ csv_threshold_str,
+ csv_output_path,
) = sys.argv
+csv_threshold = float(csv_threshold_str)
+
+print(f'loading onehot-columns.npy', file=sys.stderr)
columns = numpy.load(os.path.join(input_path, 'onehot-columns.npy'))
# pvalue maps tag# => [pvalue1, pvalue2, ...] (one het p-value and one hom p-value for each tile variant)
x.append(pow(10, -columns[4,i] / 1000000))
pvalue[tag] = x
+print(f'building tilepos dict', file=sys.stderr)
# tilepos maps tag# => (chromosome, position)
tilepos = {}
for dirent in os.scandir(input_path):
if annotation[3] == "=":
tilepos[int(annotation[0])] = (annotation[4], int(annotation[5]))
+if csv_threshold > 0 and csv_output_path != "":
+ print(f'writing csv {csv_output_path}', file=sys.stderr)
+ with open(csv_output_path, 'wt') as f:
+ for tag, chrpos in sorted(tilepos.items(), key=lambda item: (item[1][0][-1] > '9', item[1][0].lstrip('chr').zfill(2), item[1][1])):
+ for p in pvalue.get(tag, []):
+ if p < pow(10, -csv_threshold):
+ print(f'{tag},{chrpos[0]},{chrpos[1]},{p}', file=f)
+
+print(f'building series dict', file=sys.stderr)
series = {"#CHROM": [], "POS": [], "P": []}
-for tag, chrpos in sorted(tilepos.items(), key=lambda item: (item[1][0].lstrip('chr').zfill(2), item[1][1])):
+for tag, chrpos in sorted(tilepos.items(), key=lambda item: (item[1][0][-1] > '9', item[1][0].lstrip('chr').zfill(2), item[1][1])):
for p in pvalue.get(tag, []):
series["#CHROM"].append(chrpos[0])
series["POS"].append(chrpos[1])
series["P"].append(p)
-qmplot.manhattanplot(data=pandas.DataFrame(series))
-matplotlib.pyplot.savefig(output_path)
+chroms = {}
+for chrom in series["#CHROM"]:
+ chroms[chrom] = True
+chroms[None] = True
+
+print(f'generating plots', file=sys.stderr)
+for chrom in chroms.keys():
+ output_file = output_path
+ xlabel = "Chromosome"
+ if chrom:
+ output_file = f'.{chrom}.'.join(output_file.rsplit('.', 1))
+ xlabel = f'position on {chrom}'
+ qmplot.manhattanplot(data=pandas.DataFrame(series),
+ CHR=chrom,
+ color='#1D2A44,#441D2A',
+ suggestiveline=2e-10,
+ genomewideline=2e-11,
+ sign_line_cols=["#D62728", "#2CA02C"],
+ marker=".",
+ alpha = 0.6,
+ hline_kws={"linestyle": "--", "lw": 1.3},
+ title="Tile Variant Manhattan Plot",
+ xlabel=xlabel,
+ ylabel=r"$-log_{10}{(P)}$",
+ xticklabel_kws={"rotation": "vertical"})
+ matplotlib.pyplot.savefig(output_file, bbox_inches="tight")
+ matplotlib.pyplot.close()