pysamstats
A Python utility for calculating statistics against genome positions based on sequence alignments from a SAM or BAM file.
- Source: https://github.com/alimanfoo/pysamstats
- Download: http://pypi.python.org/pypi/pysamstats
- Release notes: https://github.com/alimanfoo/pysamstats/releases
Installation
The easiest way to install pysamstats is via conda, e.g.:
$ conda install -c bioconda pysamstats
Alternatively, pysamstats can be installed from source via pip.
$ pip install pysamstats
Alternatively, clone the git repo and install:
$ git clone git://github.com/alimanfoo/pysamstats.git
$ cd pysamstats
$ python setup.py install
$ nosetests -v # optional, run test suite
If you have problems installing pysam, please email the pysam user group.
N.B., some functions also require numpy and pytables to be installed.
Usage
From the command line:
$ pysamstats --help
Usage: pysamstats [options] FILE
Calculate statistics against genome positions based on sequence alignments
from a SAM or BAM file and print them to stdout.
Options:
-h, --help show this help message and exit
-t TYPE, --type=TYPE Type of statistics to print, one of: alignment_binned,
baseq, baseq_ext, baseq_ext_strand, baseq_strand,
coverage, coverage_binned, coverage_ext,
coverage_ext_binned, coverage_ext_strand, coverage_gc,
coverage_strand, mapq, mapq_binned, mapq_strand, tlen,
tlen_binned, tlen_strand, variation, variation_strand.
-c CHROMOSOME, --chromosome=CHROMOSOME
Chromosome name.
-s START, --start=START
Start position (1-based).
-e END, --end=END End position (1-based).
-z, --zero-based Use zero-based coordinates (default is false, i.e.,
use one-based coords).
-u, --truncate Truncate pileup-based stats so no records are emitted
outside the specified range.
-S STEPPER, --stepper=STEPPER
Stepper to provide to underlying pysam call. Options
are:"all" (default): all reads are returned, except
where flags BAM_FUNMAP, BAM_FSECONDARY, BAM_FQCFAIL,
BAM_FDUP set; "nofilter" applies no filter to returned
reads; "samtools": filter & read processing as in
_csamtools_ pileup. This requires a fasta file. For
complete details see the pysam documentation.
-d, --pad Pad pileup-based stats so a record is emitted for
every position (default is only covered positions).
-D MAX_DEPTH, --max-depth=MAX_DEPTH
Maximum read depth permitted in pileup-based
statistics. The default limit is 8000.
-f FASTA, --fasta=FASTA
Reference sequence file, only required for some
statistics.
-o, --omit-header Omit header row from output.
-p N, --progress=N Report progress every N rows.
--window-size=N Size of window for binned statistics (default is 300).
--window-offset=N Window offset to use for deciding which genome
position to report binned statistics against. The
default is 150, i.e., the middle of 300bp window.
--format=FORMAT Output format, one of {tsv, csv, hdf5} (defaults to
tsv). N.B., hdf5 requires PyTables to be installed.
--output=OUTPUT Path to output file. If not provided, write to stdout.
--fields=FIELDS Comma-separated list of fields to output (defaults to
all fields).
--hdf5-group=HDF5_GROUP
Name of HDF5 group to write to (defaults to the root
group).
--hdf5-dataset=HDF5_DATASET
Name of HDF5 dataset to create (defaults to "data").
--hdf5-complib=HDF5_COMPLIB
HDF5 compression library (defaults to zlib).
--hdf5-complevel=HDF5_COMPLEVEL
HDF5 compression level (defaults to 5).
--hdf5-chunksize=HDF5_CHUNKSIZE
Size of chunks in number of bytes (defaults to 2**20).
--min-mapq=MIN_MAPQ Only reads with mapping quality equal to or greater
than this value will be counted (0 by default).
--min-baseq=MIN_BASEQ
Only reads with base quality equal to or greater than
this value will be counted (0 by default). Only
applies to pileup-based statistics.
--no-dup Don't count reads flagged as duplicate.
--no-del Don't count reads aligned with a deletion at the given
position. Only applies to pileup-based statistics.
Pileup-based statistics types (each row has statistics over reads in a pileup column):
* coverage - Number of reads aligned to each genome position
(total and properly paired).
* coverage_strand - As coverage but with forward/reverse strand counts.
* coverage_ext - Various additional coverage metrics, including
coverage for reads not properly paired (mate
unmapped, mate on other chromosome, ...).
* coverage_ext_strand - As coverage_ext but with forward/reverse strand counts.
* coverage_gc - As coverage but also includes a column for %GC.
* variation - Numbers of matches, mismatches, deletions,
insertions, etc.
* variation_strand - As variation but with forward/reverse strand counts.
* tlen - Insert size statistics.
* tlen_strand - As tlen but with statistics by forward/reverse strand.
* mapq - Mapping quality statistics.
* mapq_strand - As mapq but with statistics by forward/reverse strand.
* baseq - Base quality statistics.
* baseq_strand - As baseq but with statistics by forward/reverse strand.
* baseq_ext - Extended base quality statistics, including qualities
of bases matching and mismatching reference.
* baseq_ext_strand - As baseq_ext but with statistics by forward/reverse strand.
Binned statistics types (each row has statistics over reads aligned starting within a genome window):
* coverage_binned - As coverage but binned.
* coverage_ext_binned - As coverage_ext but binned.
* mapq_binned - Similar to mapq but binned.
* alignment_binned - Aggregated counts from cigar strings.
* tlen_binned - As tlen but binned.
Examples:
pysamstats --type coverage example.bam > example.coverage.txt
pysamstats --type coverage --chromosome Pf3D7_v3_01 --start 100000 --end 200000 example.bam > example.coverage.txt
Version: 1.1.2 (pysam 0.15.1)
From Python:
import pysam
import pysamstats
mybam = pysam.AlignmentFile('/path/to/your/bamfile.bam')
# iterate over statistics, one record at a time
for rec in pysamstats.stat_coverage(mybam, chrom='Pf3D7_01_v3', start=10000, end=20000):
print rec['chrom'], rec['pos'], rec['reads_all'], rec['reads_pp']
...For convenience, functions are provided for loading data directly into numpy arrays, e.g.:
import pysam
import pysamstats
import matplotlib.pyplot as plt
mybam = pysam.AlignmentFile('/path/to/your/bamfile.bam')
a = pysamstats.load_coverage(mybam, chrom='Pf3D7_01_v3', start=10000, end=20000)
plt.plot(a.pos, a.reads_all)
plt.show()For pileup-based statistics functions, note the following:
- By default a row is emitted for all genome positions covered by reads overlapping the selected region. This means rows will be emitted for positions outside the selected region, but statistics may not be accurate as not all reads overlapping that position will have been counted. To truncate output to exactly the selected region, provide a
truncate=Truekeyword argument. - By default a row is only emitted for genome positions covered by at least one read. To emit a row for every genome position, provide a
pad=Truekeyword argument. - By default the number of reads in a pileup column is limited to 8000. To increase this limit, provide a
max_depth=100000keyword argument (or whatever number is suitable for your situation).
Field definitions
The suffix _fwd means the field is restricted to reads mapped to the forward strand, and _rev means the field is restricted to reads mapped to the reverse strand. E.g., reads_fwd means the number of reads mapped to the forward strand.
The suffix _pp means the field is restricted to reads flagged as properly paired.
-
chrom - Chromosome name.
-
pos - Position within chromosome. One-based by default when using the command line, zero-based by default when using the python API.
-
reads_all - Number of reads aligned at the position. N.b., this is really the total, i.e., includes reads where the mate is unmapped or otherwise not properly paired.
-
reads_pp - Number of reads flagged as properly paired by the aligner.
-
reads_mate_unmapped - Number of reads where the mate is unmapped.
-
reads_mate_other_chr - Number of reads where the mate is mapped to another chromosome.
-
reads_mate_same_strand - Number of reads where the mate is mapped to the same strand.
-
reads_faceaway - Number of reads where the read and its mate are mapped facing away from each other.
-
reads_softclipped - Number of reads where there is some softclipping at some point in the read's alignment (not necessarily at this position).
-
reads_duplicate - Number of reads that are flagged as duplicate.
-
gc - Percentage GC content in the reference at this position (depends on window length and offset specified).
-
matches - Number of reads where the aligned base matches the reference.
-
mismatches - Number of reads where the aligned base does not match the reference (but is not a deletion).
-
deletions - Number of reads where there is a deletion in the alignment at this position.
-
insertions - Number of reads where there is an insertion in the alignment at this position.
-
A/C/T/G/N - Number of reads where the aligned base is an A/C/T/G/N.
-
mean_tlen - Mean value of outer distance between reads and their mates for paired reads aligned at this position. N.B., leftmost reads in a pair have a positive tlen, rightmost reads have a negative tlen, so if there is no strand bias, this value should be 0.
-
rms_tlen - Root-mean-square value of outer distance between reads and their mates for paired reads aligned at this position.
-
std_tlen - Standard deviation of outer distance between reads and their mates for paired reads aligned at this position.
-
reads_mapq0 - Number of reads where mapping quality is zero.
-
rms_mapq - Root-mean-square mapping quality for reads aligned at this position.
-
max_mapq - Maximum value of mapping quality for reads aligned at this position.
-
rms_baseq - Root-mean-square value of base qualities for bases aligned at this position.
-
rms_baseq_matches - Root-mean-square value of base qualities for bases aligned at this position where the base matches the reference.
-
rms_baseq_mismatches - Root-mean-square value of base qualities for bases aligned at this position where the base does not match the reference.
Release notes
1.1.2
- Fix missing numpy as install requirement.
1.1.1
- Fix missing pyproject.toml in source distribution.
1.1.0
-
Appropriate size dtype for chromosome names is now determined dynamically, no need to manually configure for longer chromosome/contig names. By Nick Harding, #72, #74.
-
Expose 'stepper' option via Python and command line API, to allow setting of different pileup behaviours. By Nick Harding, #78, #86.
-
Expose options
min_mapq,min_baseq,no_del,no_dupvia load_*() functions. By nrkssa, #93. -
Add pyproject.toml for package build requirements, which means that there is no need to manually install pysam before installing pysamstats via pip. By Michiel Vermeir, #97.
-
Added a regression test to ensure consistent outputs in future package versions. By Nick Harding, #79.
-
Pysam dependency upgraded to 0.15.
1.0.1
- Changed output of deletions field in variation stats to exclude RNA reads aligned with a splice ("N" in cigar) (#65)
1.0.0
- Upgrades for compatibility with pysam 0.11.
- Added options for filtering reads based on mapping quality, base quality, deletion status and duplicate flag.
