def test_from_existing_bam(self):
bam_path = get_sample_data(Path("mbf_align/ex2.bam"))
bam_job = ppg.FileInvariant(bam_path)
genome = object()
lane = mbf_align.AlignedSample("test_lane", bam_job, genome, False,
"AA123")
assert lane.name == "test_lane"
assert lane.load()[0] is bam_job
assert isinstance(lane.load()[1], ppg.FileInvariant)
assert lane.genome is genome
assert not lane.is_paired
assert lane.vid == "AA123"
with pytest.raises(ValueError):
mbf_align.AlignedSample("test_lane", bam_job, genome, False,
"AA123")
lane2 = mbf_align.AlignedSample("test_lane2", bam_job, genome, True,
"AA123")
assert lane2.is_paired
b = lane.get_bam()
assert isinstance(b, pysam.Samfile)
b = lane.get_unique_aligned_bam()
assert isinstance(b, pysam.Samfile)
assert lane.get_bam_names()[0] == bam_path
assert lane.get_bam_names()[1] == bam_path + ".bai"
assert lane.mapped_reads() == 8
assert lane.unmapped_reads() == 0
for job in get_qc_jobs():
assert job._pruned
def test_subtraction_by_read(self):
from mbf_sampledata import get_human_22_fake_genome
genome = get_human_22_fake_genome()
lane = mbf_align.AlignedSample(
"test_lane",
get_sample_data(Path("mbf_align/rnaseq_spliced_chr22.bam")),
genome,
False,
"AA123",
) # index creation is automatic
lane2 = mbf_align.AlignedSample(
"test_lane2",
get_sample_data(Path("mbf_align/rnaseq_spliced_chr22.bam")),
genome,
False,
"AA124",
) # index creation is automatic
lane3 = mbf_align.AlignedSample(
"test_lane3",
get_sample_data(Path("mbf_align/chipseq_chr22.bam")),
genome,
False,
"AA123",
) # index creation is automatic
lane3_subset = mbf_align.AlignedSample(
"test_lane3_subset",
get_sample_data(Path("mbf_align/chipseq_chr22_subset.bam")),
genome,
False,
"AA123",
) # index creation is automatic
lane_empty = lane.post_process(
mbf_align.post_process.SubtractOtherLane(lane2), new_name="empty")
lane_full = lane.post_process(
mbf_align.post_process.SubtractOtherLane(lane3), new_name="full")
lane_some = lane3.post_process(
mbf_align.post_process.SubtractOtherLane(lane3_subset),
result_dir="results/aligned/shu",
)
qc_jobs = [
lane_some.post_processor_qc_jobs, lane_full.post_processor_qc_jobs
]
prune_qc(lambda job: job in qc_jobs)
ppg.run_pipegraph()
assert Path(lane_empty.get_bam_names()[1]).exists()
assert Path(lane_full.get_bam_names()[1]).exists()
assert lane_empty.mapped_reads() == 0
assert lane_full.mapped_reads() == lane.mapped_reads()
assert lane.mapped_reads() != 0
assert (lane_some.mapped_reads() == lane3.mapped_reads() -
lane3_subset.mapped_reads())
assert lane3_subset.mapped_reads(
) # make sure there was something to subtract
assert "shu" in lane_some.get_bam_names()[0]
assert_image_equal(qc_jobs[0].filenames[0], "_result_dir")
assert_image_equal(qc_jobs[0].filenames[0])
def test_to_fastq(self):
bam_path = get_sample_data(Path("mbf_align/ex2.bam"))
bam_job = ppg.FileInvariant(bam_path)
genome = object()
lane = mbf_align.AlignedSample("test_lane", bam_job, genome, False,
"AA123")
fastq_path = "out.fastq"
lane.to_fastq(fastq_path)
ppg.run_pipegraph()
assert Path(fastq_path).exists()
assert (Path(fastq_path).read_text() == """@read_28833_29006_6945
AGCTTAGCTAGCTACCTATATCTTGGTCTTGGCCG
+
<<<<<<<<<<<<<<<<<<<<<:<9/,&,22;;<<<
@read_28701_28881_323b
TGCAAGGCCGCATCGGCCAAGGCCAAGATATAGGT
+
<<<<7<<<<<<<<<<<<;6<<<:;7<<<<;<<<<<
@read_28701_28881_323c
TGCAAGGCCGCATCGGCCAAGGCCAAGATATAGGT
+
<<<<7<<<<<<<<<<<<;6<<<:;7<<<<;<<<<<
@read_28701_28881_324a
TGCAAGGCCGCATCGGCCAAGGCCAAGATATAGGT
+
<<<<7<<<<<<<<<<<<;6<<<:;7<<<<;<<<<<
@read_28701_28881_324b
TGCAAGGCCGCATCGGCCAAGGCCAAGATATAGGT
+
<<<<7<<<<<<<<<<<<;6<<<:;7<<<<;<<<<<
@read_28701_28881_324c
TGCAAGGCCGCATCGGCCAAGGCCAAGATATAGGT
+
<<<<7<<<<<<<<<<<<;6<<<:;7<<<<;<<<<<
@test_clipped1
AGCTTAGCTAGCTACCTATATCTTGGTCTTGGCCG
+
<<<<<<<<<<<<<<<<<<<<<:<9/,&,22;;<<<
@test_clipped1
AGCTTAGCTAGCTACCTATATCTTGGTCTTGGCCG
+
<<<<<<<<<<<<<<<<<<<<<:<9/,&,22;;<<<
""")
lane2 = mbf_align.AlignedSample("test_lane2",
bam_job,
genome,
is_paired=True,
vid="AA123")
with pytest.raises(ValueError):
lane2.to_fastq(
"nope.fastq") # no support for paired end data at this point
def prep_lane(self):
from mbf_sampledata import get_human_22_fake_genome
# straight from chr22 of the human genome
genome = get_human_22_fake_genome()
lane = mbf_align.AlignedSample(
"test_lane",
get_sample_data(Path("mbf_align/rnaseq_spliced_chr22.bam")),
genome,
False,
"AA123",
)
return lane
def test_chromosome_mapping(self):
bam_path = get_sample_data(Path("mbf_align/ex2.bam"))
bam_job = ppg.FileInvariant(bam_path)
genome = DummyGenome()
lane = mbf_align.AlignedSample("test_lane", bam_job, genome, False,
"AA123")
assert lane.name == "test_lane"
assert lane.load()[0] is bam_job
assert isinstance(lane.load()[1], ppg.FileInvariant)
assert lane.genome is genome
assert not lane.is_paired
assert lane.vid == "AA123"
with pytest.raises(ValueError):
mbf_align.AlignedSample("test_lane", bam_job, genome, False,
"AA123")
lane2 = mbf_align.AlignedSample("test_lane2", bam_job, genome, True,
"AA123")
assert lane2.is_paired
b = lane.get_bam()
assert isinstance(b, pysam.Samfile)
b
def gatk_test_lanes():
genome_human = mbf_genomes.EnsemblGenome("Homo_sapiens", 96)
input_samples = [
[
mbf_align.AlignedSample(
"Test1GATK",
"/project/code/mvariants/data/base_raw_test_hg36_Subread_gatk_rg.bam",
genome_human,
is_paired=False,
vid=None,
)
],
[
mbf_align.AlignedSample(
"Test2GATK",
"data/base_raw_test_hg3612_Subread_gatk_rg.bam",
genome_human,
is_paired=False,
vid=None,
)
],
]
return input_samples
def test_missing_index_file(self):
bam_path = get_sample_data(Path("mbf_align/ex2.bam"))
no_index = "noindex.bam"
shutil.copy(bam_path, no_index)
genome = object()
lane = mbf_align.AlignedSample("test_lane", no_index, genome, False,
"AA123")
assert isinstance(lane.load()[0], ppg.FileInvariant)
assert isinstance(lane.load()[1], ppg.FileGeneratingJob)
assert lane.load()[1].job_id != "noindex.bam.bai"
assert lane.load()[0] in lane.load()[1].prerequisites
with pytest.raises(FileNotFoundError):
lane.mapped_reads()
ppg.run_pipegraph()
assert lane.mapped_reads() == 8
def test_creating_index_for_fg_job(self):
def gen():
shutil.copy(get_sample_data(Path("mbf_align/ex2.bam")),
"sample.bam")
ppg.util.global_pipegraph.quiet = False
job = ppg.FileGeneratingJob("sample.bam", gen)
genome = object()
lane = mbf_align.AlignedSample("test_lane", job, genome, False,
"AA123")
assert isinstance(lane.load()[1], ppg.FileGeneratingJob)
assert lane.load()[0] in lane.load()[1].prerequisites
ppg.run_pipegraph()
assert Path("sample.bam").exists()
assert Path("sample.bam.bai").exists()
def test_lane_invariants_on_string(self):
bam_path = get_sample_data(Path("mbf_align/ex2.bam"))
genome = object()
lane = mbf_align.AlignedSample("test_lane", bam_path, genome, False,
"AA123")
assert isinstance(lane.load()[0], ppg.FileInvariant)
def test_lane_raises_on_multifilegeneratingJobWithNoBAM(self):
mfg = ppg.MultiFileGeneratingJob(["a.sam"], lambda: 5)
genome = object()
with pytest.raises(ValueError):
mbf_align.AlignedSample("test_lane", mfg, genome, False, "AA123")
def test_lane_invariants_on_non_accepted_value(self):
genome = object()
with pytest.raises(ValueError):
mbf_align.AlignedSample("test_lane", 123, genome, False, "AA123")
def test_alignment_stats(self):
from mbf_sampledata import get_human_22_fake_genome
genome = get_human_22_fake_genome()
lane = mbf_align.AlignedSample(
"test_lane",
get_sample_data(Path("mbf_align/rnaseq_spliced_chr22.bam")),
genome,
False,
"AA123",
) # index creation is automatic
counts = {"get_bam": 0}
def get_bam():
counts["get_bam"] += 1
class DummySam:
mapped = 5
unmapped = 10
def __enter__(self):
return self
def __exit__(self, *args):
pass
return DummySam()
lane.get_bam = get_bam
assert lane.get_alignment_stats() == {"Mapped": 5, "Unmapped": 10}
assert counts["get_bam"] == 1
class DummyAlignerWithout:
pass
lane = mbf_align.AlignedSample(
"test_lane2",
get_sample_data(Path("mbf_align/rnaseq_spliced_chr22.bam")),
genome,
False,
"AA123",
aligner=DummyAlignerWithout(),
) # index creation is automatic
lane.get_bam = get_bam
assert counts["get_bam"] == 1
assert lane.get_alignment_stats() == {"Mapped": 5, "Unmapped": 10}
assert counts["get_bam"] == 2
class DummyAlignerWith:
def get_alignment_stats(self, bam_filename):
assert (Path(bam_filename).resolve() == get_sample_path(
"mbf_align/rnaseq_spliced_chr22.bam").resolve())
return {"Hello": 23}
lane = mbf_align.AlignedSample(
"test_lane3",
get_sample_data("mbf_align/rnaseq_spliced_chr22.bam"),
genome,
False,
"AA123",
aligner=DummyAlignerWith(),
) # index creation is automatic
lane.get_bam = get_bam
assert counts["get_bam"] == 2
assert lane.get_alignment_stats() == {"Hello": 23}
assert counts["get_bam"] == 2
