def test_read_directed_bedfile():
lines = [
"chr1\t0\t10\t.\t.\t+", "chr1\t10\t25\t.\t.\t-",
"chr1\t25\t35\t.\t.\t+", "chr2\t0\t5\t.\t.\t-", "chr2\t5\t10\t.\t.\t+"
]
f = io.StringIO("\n".join(lines))
bedfile = read_bedfile(f)
assert bedfile == {
"chr1": Regions([0, 10, 25], [10, 25, 35], [1, -1, 1]),
"chr2": Regions([0, 5], [5, 10], [-1, 1])
}
def test_read_bedfile():
lines = [
"chr1\t0\t10", "chr1\t10\t25", "chr1\t25\t35", "chr2\t0\t5",
"chr2\t5\t10"
]
f = io.StringIO("\n".join(lines))
bedfile = read_bedfile(f)
assert bedfile == {
"chr1": Regions([0, 10, 25], [10, 25, 35]),
"chr2": Regions([0, 5], [5, 10])
}
def to_regions(states, log_probs, lengths, chroms):
offsets = np.cumsum(lengths)
start = 0
regions = {}
scores = {}
peaks = {}
log_probs = log_probs[:, 1] - log_probs[:, 0]
# cumulative_log_probs = np.insert(np.cumsum(log_probs), 0, 0)
for chrom, length in zip(chroms, lengths):
dense = states[start:start + length]
local_probs = log_probs[start:start + length]
changes = np.flatnonzero(np.diff(dense)) + 1
if dense[0] == 1:
changes = np.insert(changes, 0, 0)
if dense[-1] == 1:
changes = np.append(changes, dense.size)
changes = changes.reshape((-1, 2))
regions[chrom] = Regions(changes[:, 0], changes[:, 1])
scores[chrom] = [
np.max(local_probs[start:end])
for start, end in zip(changes[:, 0], changes[:, 1])
]
peaks[chrom] = [
np.mean(np.flatnonzero(local_probs[start:end] == m)).astype(int)
for start, end, m in zip(changes[:, 0], changes[:,
1], scores[chrom])
]
# np.argmax(local_probs[start:end]) for start, end in zip(changes[:, 0], changes[:, 1])]
# cumulative_log_probs[changes[:, 1]]-cumulative_log_probs[changes[:, 0]]
return regions, scores, peaks
def test_read_genes():
lines = [
"1366 NM_026243 chr10 + 102374436 102391468 102378157 102389363 4 102374436,102378151,102385005,102388221, 102374644,102378304,102385153,102391468, 0 Mgat4c cmpl cmpl -1,0,0,1,",
"171 NM_172553 chr10 - 103007846 103028777 103009187 103028606 4 103007846,103022176,103025134,103028380, 103009508,103022305,103025439,103028777, 0 Alx1 cmpl cmpl 0,0,1,0,"
]
f = io.StringIO("\n".join(lines))
genes = read_refseq(f)["chr10"]
exon_starts = [102374436, 102378151, 102385005, 102388221
] + [103007846, 103022176, 103025134, 103028380][::-1]
exon_ends = [102374644, 102378304, 102385153, 102391468
] + [103009508, 103022305, 103025439, 103028777][::-1]
cd_starts = [
102378157 - 102378151 + 102374644 - 102374436, 103028777 - 103028606
]
cd_ends = [509 + 1142, 321 + 831]
true_genes = Genes(Regions(exon_starts, exon_ends, [1] * 4 + [-1] * 4),
[0, 4, 8],
coding_regions=Regions(cd_starts, cd_ends))
assert genes == true_genes
def regions_10b():
return Regions([2, 13, 17], [12, 23, 27], [1, -1, 1])
def test_averageplot(bedgraph, regions_10b, true_signal):
plotter = AveragePlot(8, do_normalize=False)
r = Regions(regions_10b.starts + 3, regions_10b.ends - 3,
regions_10b.directions)
signal = plotter([("chr1", bedgraph)], {"chr1": r})
assert np.all(signal["y"].values == true_signal[1:-1])
def test_tssplot(bedgraph, regions_10b, true_signal):
plotter = TSSPlot(10, 10, do_normalize=False)
mids = (regions_10b.starts + regions_10b.ends) // 2
r = Regions(mids, mids + 1, regions_10b.directions)
signal = plotter([("chr1", bedgraph)], {"chr1": r})
assert np.all(signal["y"].values == true_signal)
def regions():
return Regions([100, 200, 300, 400, 500], [101, 202, 303, 404, 505],
[1, 1, 1, 1, 1])
def regions():
regions = Regions([4, 14, 24], [10, 20, 30])
return {"chr1": regions}