- bamPlot_turbo is a set of scripts designed to create publication quality vector graphic plots of read density from nextgen sequencing data across specific genomic loci.
- Read data must be in the form of sorted and indexed BAM files
- Input regions can either be specified individually e.g.
chr1:+:1-1000
or as a batch via a .gff file.
- Reference gene annotations are also plotted. (Currently, only HG18,HG19,MM8,MM9 are supported)
- Additional reference regions can be plotted when provided in .bed format
- bamPlot_turbo is part of the bradnerLab pipeline module. Install instructions under construction
- bamPlot_turbo is called from the command line using python ./bamPlot_turbo.py
Usage: bamPlot_turbo.py [options] -g [GENOME] -b [SORTED BAMFILE(S)] -i [INPUTFILE] -o [OUTPUTFOLDER]
Options:
-h, --help show this help message and exit
-b BAM, --bam=BAM Enter a comma separated list of .bam files to be
processed.
-i INPUT, --input=INPUT
Enter .gff or genomic region e.g. chr1:+:1-1000.
-g GENOME, --genome=GENOME
specify a genome, HG18,HG19,MM8,MM9 are currently
supported
-o OUTPUT, --output=OUTPUT
Enter the output folder.
-c COLOR, --color=COLOR
Enter a colon separated list of colors e.g.
255,0,0:255,125,0, default samples the rainbow
-s SENSE, --sense=SENSE
Map to '+','-' or 'both' strands. Default maps to
both.
-e EXTENSION, --extension=EXTENSION
Extends reads by n bp. Default value is 200bp
-r, --rpm Normalizes density to reads per million (rpm) Default
is True
-y YSCALE, --yScale=YSCALE
Choose either relative or uniform y axis scaling.
options = 'relative,uniform' Default is relative
scaling
-n NAMES, --names=NAMES
Enter a comma separated list of names for your bams
-p PLOT, --plot=PLOT Choose either all lines on a single plot or multiple
plots. options = 'single,multiple'
-t TITLE, --title=TITLE
Specify a title for the output plot(s), default will
be the coordinate region
--save-temp If flagged will save temporary files made by bamPlot
--bed=BED Add a comma separated list of bam files to plot
- plotting reads from two datasets at a single genomic region
python ./bamPlot_turbo.py -g 'hg18' -b $BAM1,$BAM2 -i 'chr1:+:100900000-100980000' -r -y 'UNIFORM' -t 'VCAM1' --bed $BED1 -o './'