def test_strandness():
b = BAM(sequana_data("test_hg38_chr18.bam"))
res = b.infer_strandness(sequana_data("hg38_chr18.bed"), 200000)
assert res[0] == 'Paired-end'
assert res[1] > 0.94
assert res[2] < 0.06
assert res[3] < 0.0011
def test_alignment():
s = BAM(datatest)
# no need to call reset but does not harm and reminds us that it shoudl be
# used in general to make sure we start at the beginning of the iterator.
s.reset()
a = Alignment(next(s))
a.as_dict()
def test_alignment():
datatest = sequana_data("test.bam", "testing")
s = BAM(datatest)
# no need to call reset but does not harm and reminds us that it shoudl be
# used in general to make sure we start at the beginning of the iterator.
s.reset()
a = Alignment(next(s))
a.as_dict()
def test_cs_in_bam():
b = BAM(sequana_data("test_CS_tiny.bam"))
assert b.summary == {
'flags': {0: 2, 16: 2},
'mapq': {60: 4},
'mean_quality': 0.0,
'read_length': {1772: 1, 10779: 1, 13726: 1, 20480: 1}}
df = b.get_df_concordance()
import math
assert math.floor(df.sum().sum()) == 103769 # exact is 103769.5600734975
def test_cs_in_bam():
b = BAM(sequana_data("test_CS_tiny.bam"))
assert b.summary == {
'flags': {
0: 2,
16: 2
},
'mapq': {
60: 4
},
'mean_quality': 0.0,
'read_length': {
1772: 1,
10779: 1,
13726: 1,
20480: 1
}
}
df = b.get_df_concordance()
import math
assert math.floor(df.sum().sum()) == 103813 # exact is 103769.5600734975
def test_bam(tmpdir):
s = BAM(datatest)
assert len(s) == 1000
assert s.is_sorted is True
assert len(list(s.iter_unmapped_reads())) == 2
s.reset()
assert len(list(s.iter_mapped_reads())) == 998
s.reset()
# call this here before other computations on purpose
with TempFile(suffix=".json") as fh:
s.bam_analysis_to_json(fh.name)
assert s.get_read_names()
s.get_mapped_read_length()
s.get_stats()
s.get_full_stats_as_df()
with TempFile(suffix='.png') as fh:
s.plot_bar_flags(filename=fh.name, logy=True)
s.plot_bar_flags(filename=fh.name)
with TempFile(suffix='.png') as fh:
s.plot_bar_mapq(filename=fh.name)
with TempFile() as fh:
s.to_fastq(fh.name)
from sequana import FastQ
ff = FastQ(fh.name)
len(ff) == len(s)
s.get_gc_content()
s.get_length_count()
s.plot_gc_content()
try:
s.plot_gc_content(bins=[1, 2, 10])
assert False
except:
assert True
def test_bam_others():
b = BAM(sequana_data("measles.fa.sorted.bam"))
assert len(b) == 2998
# plot_reaqd_length and data
X, Y = b._get_read_length()
assert sum(Y) == 2623
b.plot_read_length()
b.plot_acgt_content()
b.hist_coverage()
b.plot_coverage()
b.boxplot_qualities()
b.plot_indel_dist()
def test_bam_others():
b = BAM(sequana_data("measles.fa.sorted.bam"))
assert len(b) == 2998
# plot_reaqd_length and data
X, Y = b._get_read_length()
assert sum(Y) == 2623
b.plot_read_length()
b.hist_coverage()
b.plot_coverage()
b.boxplot_qualities()
b.plot_indel_dist()
def test_bam(tmpdir):
datatest = sequana_data("test.bam", "testing")
s = BAM(datatest)
assert len(s) == 1000
assert s.is_sorted is True
df = s.get_df_concordance()
assert s.is_paired is True
assert int(df.length.sum()) == 67938
assert int(df.M.sum()) == 67788
# call this here before other computations on purpose
with TempFile(suffix=".json") as fh:
s.bam_analysis_to_json(fh.name)
assert s.get_read_names()
s.get_mapped_read_length()
s.get_stats()
s.get_full_stats_as_df()
with TempFile() as fh:
s.to_fastq(fh.name)
from sequana import FastQ
ff = FastQ(fh.name)
len(ff) == len(s)
# plotting
with TempFile(suffix='.png') as fh:
s.plot_bar_flags(filename=fh.name, logy=True)
s.plot_bar_flags(filename=fh.name)
with TempFile(suffix='.png') as fh:
s.plot_bar_mapq(filename=fh.name)
s.get_gc_content()
s.get_length_count()
s.plot_gc_content()
s.boxplot_qualities()
s.boxplot_qualities(max_sample=50)
try:
s.plot_gc_content(bins=[1,2,10])
assert False
except:
assert True
def test_bam(tmpdir):
datatest = sequana_data("test.bam", "testing")
s = BAM(datatest)
assert len(s) == 1000
assert s.is_sorted is True
df = s.get_df_concordance()
assert s.is_paired is True
assert int(df.length.sum()) == 67938
assert int(df.M.sum()) == 67788
df = s.get_df()
# call this here before other computations on purpose
with TempFile(suffix=".json") as fh:
s.bam_analysis_to_json(fh.name)
assert s.get_read_names()
s.get_mapped_read_length()
s.get_stats()
s.get_stats_full()
s.get_samtools_stats_as_df()
with TempFile() as fh:
s.to_fastq(fh.name)
from sequana import FastQ
ff = FastQ(fh.name)
len(ff) == len(s)
# plotting
with TempFile(suffix='.png') as fh:
s.plot_bar_flags(filename=fh.name, logy=True)
s.plot_bar_flags(filename=fh.name)
with TempFile(suffix='.png') as fh:
s.plot_bar_mapq(filename=fh.name)
s.get_gc_content()
s.get_length_count()
s.plot_gc_content()
s.boxplot_qualities()
s.boxplot_qualities(max_sample=50)
try:
s.plot_gc_content(bins=[1, 2, 10])
assert False
except:
assert True
def test_mRNA_inner_distance():
b = BAM(sequana_data("test_hg38_chr18.bam"))
df = b.mRNA_inner_distance(sequana_data("hg38_chr18.bed"))
# Total read pairs used 382
# mean insert size: 88.3975155279503
assert df[0]['val'].mean() > 1436 and df[0]['val'].mean() < 1437
def test_insert_size():
d1 = sequana_data("test_measles.sam", "testing")
#d2 = sequana_data("test_measles.cram", "testing")
d3 = sequana_data("test.bam", "testing")
d4 = sequana_data("test_CS_tiny.bam")
b1 = BAM(d1)
# test max_entries
assert len(b1._get_insert_size_data(10)) == 7
b1.get_estimate_insert_size(100)
b1.get_estimate_insert_size()
b1.plot_insert_size()
#b2 = BAM(d2)
#b2.get_estimate_insert_size()
b3 = BAM(d3)
b3.get_estimate_insert_size()
b4 = BAM(d4)
assert b4.get_estimate_insert_size() == 0
