Stripenn is a command line interface python package developed for detection of atchitectural stripes from chromatin conformation capture (3C) data. It implements an algorithm rooted in computer vision for demarcation and quantification of the architectural stripes. Stripenn was demonstrated to outperform existing methods, be applicable in the context of analysis of B and T lymphocytes, and to allow examination of the role of sequence variation on the architectural stripes by studying the conservation of these features in inbred strains of mice.
Allocate an interactive session and run the program.
Sample session on a GPU node:
[user@biowulf ~]$ sinteractive --mem=48g -c50 --gres=lscratch:20 [user@cn2379 ~]$ module load stripenn +] Loading singularity 3.8.4 on cn2379 [+] Loading stripenn 1.1.50Basic usage:
[user@cn2379 ~]$ stripenn --help
Usage: stripenn [OPTIONS] COMMAND [ARGS]...
Options:
--install-completion [bash|zsh|fish|powershell|pwsh]
Install completion for the specified shell.
--show-completion [bash|zsh|fish|powershell|pwsh]
Show completion for the specified shell, to
copy it or customize the installation.
--help Show this message and exit.
Commands:
compute Finds stripe coordinates from 3D genomic data
score Calculates p-value and stripiness of given stripes based on...
seeimage Draws heatmap image of given position and color saturation...
[user@cn2379 ~]$ stripenn compute --help
Usage: stripenn compute [OPTIONS]
Finds stripe coordinates from 3D genomic data
Options:
--cool TEXT Path to cool file [required]
-o, --out TEXT Path to output directory [required]
--norm TEXT Normalization method. It should be one of the column
name of Cooler.bin(). Check it with
Cooler.bins().columns (e.g., KR, VC, VC_SQRT)
[default: KR]
-k, --chrom TEXT Set of chromosomes. e.g., 'chr1,chr2,chr3', 'all'
will generate stripes from all chromosomes
[default: all]
-c, --canny FLOAT Canny edge detection parameter. [default: 2.5]
-l, --minL INTEGER Minimum length of stripe. [default: 10]
-w, --maxW INTEGER Maximum width of stripe. [default: 8]
-m, --maxpixel TEXT Percentiles of the contact frequency data to
saturate the image. Separated by comma [default:
0.95,0.96,0.97,0.98,0.99]
-n, --numcores INTEGER The number of cores will be used. [default: 72]
-p, --pvalue FLOAT P-value cutoff for stripe. [default: 0.1]
--mask TEXT Column coordinates to be masked. e.g.,
chr9:12345678-12345789 [default: 0]
-s Use if system memory is low.
--help Show this message and exit.
Download sample data:
[user@cn2379 ~]$ wget https://www.dropbox.com/s/1bb2npvrzp3by5y/BL6.DPT.chr16.mcool?dl=0 -O test.mcool --no-check-certificateRun stripenn on the sample data:
[user@cn2379 ~]$ stripenn compute --cool test.mcool::resolutions/25000 --out output_dir/ -n 50 -k 16 -m 0.95,0.96,0.97,0.98,0.99 Result will be stored in output_dir/ ####################################### Maximum pixel value calculation ... ####################################### ####################################### Expected value calculation ... ####################################### Processing Chromosome: 16 100%|███████████████████████████████████████████████████████████████████| 10/10 [00:00<00:00, 501.33it/s] ####################################### Background distribution estimation ... ####################################### 1. Calculating the number of available columns ... 100%|████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 1111.07it/s] 2. Constituting background ... 100%|████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 1625.70it/s] /opt/conda/envs/stripenn/lib/python3.9/site-packages/numpy/core/fromnumeric.py:3440: RuntimeWarning: Mean of empty slice. return _methods._mean(a, axis=axis, dtype=dtype, Elapsed time for background estimation: 0.552 min ################################################# Finding candidate stripes from each chromosome ... ################################################# Chromosome: 16 / Maximum pixel: 95.0% 100%|█████████████████████████████████████████████████████████████████| 20/20 [00:00<00:00, 29610.34it/s] Chromosome: 16 / Maximum pixel: 96.0% 100%|█████████████████████████████████████████████████████████████████| 20/20 [00:00<00:00, 15563.28it/s] Chromosome: 16 / Maximum pixel: 97.0% 100%|█████████████████████████████████████████████████████████████████| 20/20 [00:00<00:00, 22795.13it/s] Chromosome: 16 / Maximum pixel: 98.0% 100%|█████████████████████████████████████████████████████████████████| 20/20 [00:00<00:00, 22233.26it/s] Chromosome: 16 / Maximum pixel: 99.0% 100%|█████████████████████████████████████████████████████████████████| 20/20 [00:00<00:00, 33367.57it/s] ########################## Stripiness calculation ... ########################## 16 0%| | 0/244 [00:00<?, ?it/s]/opt/conda/envs/stripenn/lib/python3.9/site-packages/numpy/core/fromnumeric.py:3440: RuntimeWarning: Mean of empty slice. return _methods._mean(a, axis=axis, dtype=dtype, /opt/conda/envs/stripenn/lib/python3.9/site-packages/numpy/core/_methods.py:189: RuntimeWarning: invalid value encountered in double_scalars ret = ret.dtype.type(ret / rcount) 100%|█████████████████████████████████████████████████████████████████| 244/244 [00:00<00:00, 313.91it/s] 1.249min taken. Check the result stored in output_dir/ [user@cn2379 ~]$ ls -l output_dir -rw-r--r-- 1 user staff 180 Nov 23 10:52 result_filtered.txt -rw-r--r-- 1 user staff 26578 Nov 23 10:52 result_unfiltered.txt -rw-r--r-- 1 user staff 178 Nov 23 10:51 stripenn.logEnd the interactive session:
[user@cn2379 ~]$ exit
Create a batch input file (e.g. stripenn.sh). For example:
#!/bin/bash set -e module load stripenn stripenn compute --cool test.mcool::resolutions/25000 --out output_dir/ -n 50 -k 16 -m 0.95,0.96,0.97,0.98,0.99
Submit this job using the Slurm sbatch command.
sbatch stripenn.sh