A small Python utility for calculating statistics per genome position based on pileups from a SAM or BAM file.
Project description
pysamstats
==========
A small Python utility for calculating statistics per genome position
based on pileups from a SAM or BAM file.
* Source: https://gihub.com/alimanfoo/pysamstats
* Download: http://pypi.python.org/pypi/pysamstats (TODO)
Installation
------------
```
$ pip install --upgrade pysam pysamstats
```
Usage
-----
From the command line:
```
$ pysamstats --help
Usage: pysamstats [options] FILE
Calculate statistics per genome position based on pileups 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: coverage,
coverage_strand, coverage_ext, coverage_ext_strand,
coverage_normed, coverage_gc, coverage_normed_gc,
variation, variation_strand, tlen, tlen_strand, mapq,
mapq_strand, baseq, baseq_strand, baseq_ext,
baseq_ext_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)
-f FASTA, --fasta=FASTA
reference sequence file, only required for some
statistics
--gc-window-length=N size of window to use for %GC calculations [300]
--gc-window-offset=N window offset to use for deciding which genome
position to report %GC calculations against [150]
-o, --omit-header omit header row from output
-p N, --progress=N report progress every N rows
Supported statistics types:
* 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_normed - depth of coverage normalised by median or mean
* coverage_gc - as coverage but also includes a column for %GC
* coverage_normed_gc - as coverage_normed but also includes columns for normalisation
by %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 - baseq 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
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
```
From Python:
```python
import pysam
import pysamstats
mybam = pysam.Samfile('/path/to/your/bamfile.bam')
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']
...
```
==========
A small Python utility for calculating statistics per genome position
based on pileups from a SAM or BAM file.
* Source: https://gihub.com/alimanfoo/pysamstats
* Download: http://pypi.python.org/pypi/pysamstats (TODO)
Installation
------------
```
$ pip install --upgrade pysam pysamstats
```
Usage
-----
From the command line:
```
$ pysamstats --help
Usage: pysamstats [options] FILE
Calculate statistics per genome position based on pileups 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: coverage,
coverage_strand, coverage_ext, coverage_ext_strand,
coverage_normed, coverage_gc, coverage_normed_gc,
variation, variation_strand, tlen, tlen_strand, mapq,
mapq_strand, baseq, baseq_strand, baseq_ext,
baseq_ext_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)
-f FASTA, --fasta=FASTA
reference sequence file, only required for some
statistics
--gc-window-length=N size of window to use for %GC calculations [300]
--gc-window-offset=N window offset to use for deciding which genome
position to report %GC calculations against [150]
-o, --omit-header omit header row from output
-p N, --progress=N report progress every N rows
Supported statistics types:
* 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_normed - depth of coverage normalised by median or mean
* coverage_gc - as coverage but also includes a column for %GC
* coverage_normed_gc - as coverage_normed but also includes columns for normalisation
by %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 - baseq 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
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
```
From Python:
```python
import pysam
import pysamstats
mybam = pysam.Samfile('/path/to/your/bamfile.bam')
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']
...
```
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