def test_partitioned_read_sequences_deletion():
"""
test_partitioned_read_sequences_deletion : Test that read gets correctly
partitioned for chr1:4 TT>T where the sequence for chr1 is assumed to
be "ACCTTG"
"""
# chr1_seq = "ACCTTG"
chromosome = "chromosome"
location = 4
ref = "TT"
alt = "T"
variant = Variant(
chromosome, location, ref, alt, grch38, normalize_contig_name=False)
read = make_pysam_read(
seq="ACCTG",
cigar="4M1D1M",
mdtag="4^T1")
samfile = MockAlignmentFile(
references=(chromosome,),
reads=[read])
read_creator = ReadCollector()
variant_reads = read_creator.allele_reads_supporting_variant(
alignment_file=samfile,
variant=variant)
print(variant_reads)
assert len(variant_reads) == 1
variant_read = variant_reads[0]
expected = AlleleRead(
name=read.qname,
prefix="ACCT",
allele="",
suffix="G")
eq_(variant_read, expected)
def test_locus_reads_insertion():
"""
test_partitioned_read_sequences_insertion : Test that read gets correctly
partitioned for chr1:4 T>TG
where the sequence for chr1 is assumed to be "ACCTTG"
and the variant sequence is "ACCTGTG"
"""
variant = Variant("1", 4, ref="T", alt="TG")
pysam_read = make_pysam_read(seq="ACCTGTG", cigar="4M1I2M", mdtag="6")
samfile = MockAlignmentFile(references={"chromosome"}, reads=[pysam_read])
read_creator = ReadCollector()
reads = read_creator.get_locus_reads(samfile, "chromosome", variant.start,
variant.start)
print(reads)
assert len(reads) == 1, \
"Expected to get back one read but instead got %d" % (
len(reads),)
read = reads[0]
expected = LocusRead(
name=pysam_read.qname,
sequence=pysam_read.query_sequence,
# expect the inserted nucleotide to be missing a corresponding
# ref position
reference_positions=[0, 1, 2, 3, None, 4, 5],
quality_scores=pysam_read.query_qualities,
read_base0_start_inclusive=4,
read_base0_end_exclusive=5,
reference_base0_start_inclusive=4,
reference_base0_end_exclusive=4)
print("Actual: %s" % (read, ))
print("Expected: %s" % (expected, ))
assert_equal_fields(read, expected)
def test_locus_reads_deletion():
"""
test_partitioned_read_sequences_deletion : Test that read gets correctly
partitioned for chr1:4 TT>T where the sequence for chr1 is assumed to
be "ACCTTG"
"""
# normalization of this variant will turn it into the deletion of
# "T" at base-1 position 5
variant = Variant("1", 4, ref="TT", alt="T")
pysam_read = make_pysam_read(seq="ACCTG", cigar="4M1D1M", mdtag="4^T1")
samfile = MockAlignmentFile(references={"chromosome"}, reads=[pysam_read])
read_creator = ReadCollector()
reads = read_creator.get_locus_reads(samfile, "chromosome",
variant.start - 1, variant.start)
print(reads)
assert len(reads) == 1, \
"Expected to get back one read but instead got %d" % (
len(reads),)
read = reads[0]
expected = LocusRead(
name=pysam_read.qname,
sequence=pysam_read.query_sequence,
reference_positions=[0, 1, 2, 3, 5],
quality_scores=pysam_read.query_qualities,
# missing would have gone after 4th nucleotide in the read
read_base0_start_inclusive=4,
read_base0_end_exclusive=4,
reference_base0_start_inclusive=4,
reference_base0_end_exclusive=5)
assert_equal_fields(read, expected)
def test_locus_reads_snv():
"""
test_partitioned_read_sequences_snv : Test that read gets correctly
partitioned for chr1:4 T>G where the sequence for chr1 is assumed
to be "ACCTTG"
"""
# chr1_seq = "ACCTTG"
variant = Variant("1", 4, ref="T", alt="G")
pysam_read = make_pysam_read(seq="ACCGTG", cigar="6M", mdtag="3G2")
samfile = MockAlignmentFile(references=("chromosome", ),
reads=[pysam_read])
read_creator = ReadCollector()
reads = read_creator.get_locus_reads(samfile, "chromosome",
variant.start - 1, variant.start)
print(reads)
assert len(reads) == 1, \
"Expected to get back one read but instead got %d" % (
len(reads),)
read = reads[0]
expected = LocusRead(name=pysam_read.qname,
sequence=pysam_read.query_sequence,
reference_positions=[0, 1, 2, 3, 4, 5],
quality_scores=pysam_read.query_qualities,
reference_base0_start_inclusive=3,
reference_base0_end_exclusive=4,
read_base0_start_inclusive=3,
read_base0_end_exclusive=4)
assert_equal_fields(read, expected)
def test_locus_reads_substitution_shorter():
# test CC>G subsitution at 2nd and 3rd nucleotides of reference sequence
# "ACCTTG", for which the alignment is interpreted as a C>G variant
# followed by the deletion of a C
variant = Variant("1", 2, ref="CC", alt="G")
print(variant)
pysam_read = make_pysam_read(seq="AGTTG", cigar="2M1D3M", mdtag="1C^C4")
samfile = MockAlignmentFile(references={"chromosome"}, reads=[pysam_read])
read_creator = ReadCollector()
reads = read_creator.get_locus_reads(samfile, "chromosome", 1, 3)
assert len(reads) == 1, \
"Expected to get back one read but instead got %d" % (
len(reads),)
print(reads)
read = reads[0]
expected = LocusRead(name=pysam_read.qname,
sequence=pysam_read.query_sequence,
reference_positions=[0, 1, 3, 4, 5],
quality_scores=pysam_read.query_qualities,
read_base0_start_inclusive=1,
read_base0_end_exclusive=2,
reference_base0_start_inclusive=1,
reference_base0_end_exclusive=3)
assert_equal_fields(read, expected)
def variants_to_protein_sequences_dataframe(
expressed_vcf="data/b16.f10/b16.expressed.vcf",
not_expressed_vcf="data/b16.f10/b16.not-expressed.vcf",
tumor_rna_bam="data/b16.f10/b16.combined.sorted.bam",
min_mapping_quality=0,
max_protein_sequences_per_variant=1,
variant_sequence_assembly=False):
"""
Helper function to load pair of VCFs and tumor RNA BAM
and use them to generate a DataFrame of expressed variant protein
sequences.
"""
expressed_variants = load_vcf(expressed_vcf)
not_expressed_variants = load_vcf(not_expressed_vcf)
combined_variants = VariantCollection(
list(expressed_variants) + list(not_expressed_variants))
alignment_file = load_bam(tumor_rna_bam)
read_collector = ReadCollector(min_mapping_quality=min_mapping_quality)
read_evidence_gen = read_collector.read_evidence_generator(
variants=combined_variants, alignment_file=alignment_file)
creator = ProteinSequenceCreator(
max_protein_sequences_per_variant=max_protein_sequences_per_variant,
variant_sequence_assembly=variant_sequence_assembly)
protein_sequences_generator = \
creator.protein_sequences_from_read_evidence_generator(read_evidence_gen)
df = protein_sequences_generator_to_dataframe(protein_sequences_generator)
return df, expressed_variants, combined_variants
def test_locus_reads_substitution_longer():
# test C>GG subsitution at second nucleotide of reference sequence "ACCTTG",
# the alignment is interpreted as a C>G variant followed by an insertion of
# another G
variant = Variant("1", 2, ref="C", alt="GG")
print(variant)
pysam_read = make_pysam_read(seq="AGGCTTG", cigar="2M1I4M", mdtag="1C4")
samfile = MockAlignmentFile(references={"chromosome"}, reads=[pysam_read])
read_creator = ReadCollector()
reads = read_creator.get_locus_reads(samfile, "chromosome", 1, 2)
print(reads)
assert len(reads) == 1, \
"Expected to get back one read but instead got %d" % (
len(reads),)
read = reads[0]
expected = LocusRead(name=pysam_read.qname,
sequence=pysam_read.query_sequence,
reference_positions=[0, 1, None, 2, 3, 4, 5],
quality_scores=pysam_read.query_qualities,
read_base0_start_inclusive=1,
read_base0_end_exclusive=3,
reference_base0_start_inclusive=1,
reference_base0_end_exclusive=2)
assert_equal_fields(read, expected)
def test_assemble_transcript_fragments_snv():
alignment_file = load_bam("data/cancer-wgs-primary.chr12.bam")
chromosome = "chr12"
base1_location = 65857041
ref = "G"
alt = "C"
variant = Variant(contig=chromosome,
start=base1_location,
ref=ref,
alt=alt,
ensembl=ensembl_grch38)
read_creator = ReadCollector()
variant_reads = read_creator.allele_reads_supporting_variant(
variant=variant, alignment_file=alignment_file)
sequences = iterative_overlap_assembly(
initial_variant_sequences_from_reads(variant_reads),
min_overlap_size=30)
assert len(sequences) > 0
max_read_length = max(len(r) for r in variant_reads)
for s in sequences:
print("%s%s%s weight=%d length=%d" %
(s.prefix, s.alt, s.suffix, len(s.reads), len(s.sequence)))
eq_(s.alt, alt)
if len(s.read_names) > 1:
# expect sequences supported by more than one read to be greater
# than the read length
assert len(s) > max_read_length, \
"Expected assembled sequences to be longer than read length (%d)" % (
max_read_length,)
def test_somatic_variant_with_2_supporting_rna_reads():
variant = Variant("14", 105849746, "G", "A", grch38)
base_dir = "data/somatic-variant-with-2-supporting-rna-reads/"
normal_reads = load_bam(base_dir +
"normal.14.105849746.G.A.no-alt.sorted.bam")
tumor_reads = load_bam(base_dir +
"tumor.14.105849746.G.A.many-alt.sorted.bam")
rna_reads = load_bam(base_dir + "rna.14.105849746.G.A.2-alt.sorted.bam")
read_creator = ReadCollector()
normal_sample_variant_reads = read_creator.allele_reads_supporting_variant(
variant=variant, alignment_file=normal_reads)
eq_(len(normal_sample_variant_reads), 0)
print(normal_sample_variant_reads)
tumor_sample_variant_reads = read_creator.allele_reads_supporting_variant(
variant=variant, alignment_file=tumor_reads)
print(tumor_sample_variant_reads)
eq_(len(tumor_sample_variant_reads), 8)
rna_sample_variant_reads = read_creator.allele_reads_supporting_variant(
variant=variant, alignment_file=rna_reads)
print(rna_sample_variant_reads)
eq_(len(rna_sample_variant_reads), 2)
# Arun went through the hassle of pulling out the exact read names
# in IGV
expected_variant_rna_read_names = {
"K00193:50:H5NKVBBXX:5:2202:6421:24964",
"K00193:50:H5NKVBBXX:5:2119:30908:1138",
}
for variant_read in rna_sample_variant_reads:
assert variant_read.name in expected_variant_rna_read_names
def test_variants_to_protein_sequences_dataframe_filtered_all_reads_by_mapping_quality(
):
# since the B16 BAM has all MAPQ=255 values then all the reads should get dropped
# if we set the minimum quality to 256
variants = load_vcf("data/b16.f10/b16.vcf")
alignment_file = load_bam("data/b16.f10/b16.combined.sorted.bam")
read_collector = ReadCollector(min_mapping_quality=256)
read_evidence_gen = read_collector.read_evidence_generator(
variants=variants, alignment_file=alignment_file)
creator = ProteinSequenceCreator(max_protein_sequences_per_variant=1, )
protein_sequences_generator = creator.protein_sequences_from_read_evidence_generator(
read_evidence_gen)
df = protein_sequences_generator_to_dataframe(protein_sequences_generator)
print(df)
eq_(len(df), 0, "Expected 0 entries, got %d: %s" % (len(df), df))
def test_protein_sequence_creator_protein_length():
variants = load_vcf("data/b16.f10/b16.vcf")
alignment_file = load_bam("data/b16.f10/b16.combined.sorted.bam")
read_collector = ReadCollector()
for desired_length in [21, 15, 10]:
creator = ProteinSequenceCreator(
max_protein_sequences_per_variant=1,
protein_sequence_length=desired_length)
read_evidence_gen = read_collector.read_evidence_generator(
variants=variants, alignment_file=alignment_file)
protein_sequences_generator = creator.protein_sequences_from_read_evidence_generator(
read_evidence_gen)
df = protein_sequences_generator_to_dataframe(
protein_sequences_generator)
print(df)
protein_sequences = df["amino_acids"]
print(protein_sequences)
protein_sequence_lengths = protein_sequences.str.len()
assert (protein_sequence_lengths == desired_length).all(), (
protein_sequence_lengths, )
def test_sequence_counts_snv():
samfile = load_bam("data/cancer-wgs-primary.chr12.bam")
chromosome = "chr12"
base1_location = 65857041
ref = "G"
alt = "C"
variant = Variant(chromosome, base1_location, ref, alt, grch38)
read_creator = ReadCollector()
variant_reads = read_creator.allele_reads_supporting_variant(
alignment_file=samfile, variant=variant)
variant_sequence_creator = VariantSequenceCreator(
preferred_sequence_length=61)
variant_sequences = variant_sequence_creator.reads_to_variant_sequences(
variant=variant, reads=variant_reads)
assert len(variant_sequences) == 1
for variant_sequence in variant_sequences:
print(variant_sequence)
eq_(variant_sequence.alt, alt)
eq_(len(variant_sequence.prefix), 30)
eq_(len(variant_sequence.suffix), 30)
eq_(
variant_sequence.prefix + variant_sequence.alt +
variant_sequence.suffix, variant_sequence.sequence)
def test_somatic_variant_with_0_supporting_rna_reads():
variant = Variant("6", 90411765, "G", "A", grch38)
base_dir = "data/somatic-variant-with-0-supporting-rna-reads/"
normal_reads = load_bam(base_dir + "normal.6.90411765.G.A.sorted.bam")
tumor_reads = load_bam(base_dir + "tumor.6.90411765.G.A.sorted.bam")
rna_reads = load_bam(base_dir + "rna.6.90411765.G.A.sorted.bam")
read_creator = ReadCollector()
normal_sample_variant_reads = read_creator.allele_reads_supporting_variant(
variant=variant,
alignment_file=normal_reads)
eq_(len(normal_sample_variant_reads), 0)
print(normal_sample_variant_reads)
tumor_sample_variant_reads = read_creator.allele_reads_supporting_variant(
variant=variant,
alignment_file=tumor_reads)
print(tumor_sample_variant_reads)
eq_(len(tumor_sample_variant_reads), 5)
rna_sample_variant_reads = read_creator.allele_reads_supporting_variant(
variant=variant,
alignment_file=rna_reads)
print(rna_sample_variant_reads)
eq_(len(rna_sample_variant_reads), 0)
