A python script to plot gene coverage and IP peaks with standard deviations calculated from multiple replicates. [covfʌzeɪ]
Note: up until v0.1.3, coverage has been calculated using bedtools coverage -d. This considers gaps across positions as +1 reads. Future versions will migrate to other (preferably faster) methods that don't count gaps.
usage: covfuzze [-h] [-g GENE] [-o OUT] --bams BAMS [BAMS ...] --bed BED [--gtf GTF] [-p PEAKS] -l LABELS [LABELS ...] [-n NSUBPLOTS] [--normalize] [--scale]
Now requires python3 for compatibility with current versions of seaborn!
- numpy, tested with 1.11.1
- pysam, tested with 0.9.1
- pandas, tested with 0.18.1
- seaborn, tested with 0.7.1
- matplotlib, tested with 2.0.2 - requires macosx backend to run on mac and may have issues with pip install - try conda
- pybedtools, tested with 0.7.10 - requires bedtools available in path It requires quite a bit of memory to run with whole genome bam files. If running on a cluster, recommend allocating 200GB.
Easiest way:
pip install covfuzze
If you have issues with dependencies, try installing them separately with conda or as appropriate for your OS
-o OUT, --out OUT output prefix (incl. dir)
--bams BAMS [BAMS ...]
bam files (separated by spaces)
--bed BED bed file for region(s) of interest
-l LABELS [LABELS ...], --labels LABELS [LABELS ...]
labels associated with bams - if replicates, use same
labels
-h, --help show this help message and exit
-g GENE, --gene GENE gene name (default = GeneDoe)
--gtf GTF gtf file for gene to plot cds as shaded regions separated by exon
-p PEAKS, --peaks PEAKS
bed file with peaks
-n NSUBPLOTS, --nsubplots NSUBPLOTS
number of subplots- bams will be split evenly based on
the order given (default = 1)
--normalize normalize by gene length/summed coverage (default = False)
--scale scale y axis separately for each subplot (default = False)
covfuzze -o $outdir/$prefix --bams
alignments/sample_1_Input.sample.star.bam alignments/sample_1_IP.sample.star.bam
alignments/sample_2_Input.sample.star.bam alignments/sample_2_IP.sample.star.bam
alignments/sample_3_Input.sample.star.bam alignments/sample_3_IP.sample.star.bam
--bed ${gene}_exons.bed
-l sample_Input sample_IP sample_Input sample_IP sample_Input sample_IP
--gene ${gene} -n 1 --scale
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