https://github.com/yhoogstrate/bam-lorenz-coverage
Generate Lorenz plots and Coverage plots directly from BAM files
https://github.com/yhoogstrate/bam-lorenz-coverage
dna-seq ginicoverage lorenz ngs quality-control rna-seq wgs
Last synced: 6 months ago
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Generate Lorenz plots and Coverage plots directly from BAM files
- Host: GitHub
- URL: https://github.com/yhoogstrate/bam-lorenz-coverage
- Owner: yhoogstrate
- License: gpl-3.0
- Created: 2018-09-04T12:13:08.000Z (almost 8 years ago)
- Default Branch: master
- Last Pushed: 2021-12-07T08:03:01.000Z (over 4 years ago)
- Last Synced: 2025-01-20T17:44:26.664Z (over 1 year ago)
- Topics: dna-seq, ginicoverage, lorenz, ngs, quality-control, rna-seq, wgs
- Language: Python
- Homepage:
- Size: 313 KB
- Stars: 9
- Watchers: 2
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- Changelog: Changelog
- License: LICENSE
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README
bam-lorenz-coverage
===================
This is a free software package that very easily allows you to generate
Lorenz plots and Coverage plots, directly from a BAM file. It can also
output the tables as text documents so you can generate custom plots.
There is also support to only analyse specific regions.
Implemented in:
* Python3 + Matplotlib + Pysam
### Citing bam-lorenz-coverage ###
When using bam-lorenz-coverage for scientific applications, please
cite the following manuscript:
[10.1093/gigascience/giab080](http://dx.doi.org/10.1093/gigascience/giab080)
```
Hoogstrate Y; Komor MA; Böttcher R; van Riet J; van de Werken HJG;
van Lieshout S; Hoffmann R; van den Broek E; Bolijn AS; Dits N; Sie D;
van der Meer D; Pepers F; Bangma CH; van Leenders GJLH; Smid M;
French PJ; Martens JWM; van Workum W; van der Spek PJ; Janssen B;
Caldenhoven E; Rausch C; de Jong M; Stubbs AP; Meijer GA; Fijneman RJA;
Jenster GW:
Fusion transcripts and their genomic breakpoints in poly(A)+ and
rRNA-minus RNA sequencing data. GigaScience (2021).
http://dx.doi.org/10.1093/gigascience/giab080
```
This will indirectly help me further maintaining this software package.
Thank you in advance, Youri
### Note (how this works) ####
By the time of writing, pysam.tools.depth could not write sequentially
to a python variable. As work around, the tools spawns one thread
writing the output of pysam.tools.depth to a FIFO (named pipe) in the
/tmp folder whereas the other thread parses this FIFO. This is why the
tool runs two parallel threads.
## Installation: ##
```
$ git clone https://github.com/yhoogstrate/bam-lorenz-coverage.git
$ cd bam-lorenz-coverage
$ virtualenv -p python3 .venv
$ source .venv/bin/activate
$ python setup.py install
$ bam-lorenz-coverage --help
```
Possible issues:
- pysam is currently incompatible with python 3.7 - manual installation of pysam is still possible (git clone + python setup.py install)
* This issue has been resolved
- matplotlib depends on Tk but does not throw an error if it is missing during installation, only at runtime
* debian/ubuntu: sudo apt-get install python3-tk
* arch: pacman -Sy tk
## Usage: ##
```
Usage: bam-lorenz-coverage [OPTIONS] INPUT_ALIGNMENT_FILE
Options:
--version Show the version and exit.
-l, --lorenz-table TEXT Output table Lorenz-curve (for stdout use: -)
-c, --coverage-table TEXT Output table Coverage-graph (for stdout use: -)
-L, --lorenz-svg TEXT Output figure Lorenz-curve (SVG).
-C, --coverage-svg TEXT Output figure Coverage-graph (SVG).
-s, --stats TEXT Output additional stats to text-file
-r, --region TEXT Scan depth only in selected region
(all positions: 1-based)
-b, --bed-regions TEXT Scan depth only in selected positions or regions
(BED file: start: 0-based & end: 1-based)
--help Show this message and exit.
```
The lowercase arguments (-l, -c) allow extraction of the raw data tables for custom plotting. The uppercase arguments (-L, -C) directly generate a plot. The implemented plot only contains one sample per plot. For multi-sample plots, use the column tables and your imagination.
## Examples: ##
### Default: ###
The default SVG output figures (`-C`, `-L`) show one sample per figure, and look as follows:
### Custom, using the tables: ###
Using the output tables (`-l`, `-c`) you can also create custom plots, for instance:
