Command-line interface to the lanceotron deep learning peak caller
Project description
LanceOTron CLI
A bare-bones interface to the trained LanceOTron (LoT) model from the command line.
Installation
pip install lanceotron
Local installation
- Clone the repository.
- Install dependencies with pip.
- Install the package.
- Run tests to ensure that everything is working.
git clone git@github.com:Chris1221/lanceotron.git; cd lanceotron # Step 1
pip install -r requirements.txt # Step 2
pip install -e . # Step 3
python -m unittest
Usage
To see available commands, use the --help
flag.
lanceotron --help
Call Peaks
To call peaks from a bigWig track, use the callPeaks
command.
Option | Description | Default |
---|---|---|
file | BigWig Track to analyse | |
-t, --threshold | Threshold for selecting candidate peaks | 4 |
-w, --window | Window size for rolling mean to select candidate peaks | 400 |
-f, --folder | Output folder | "./" |
--skipheader | Skip writing the header | False |
Call Peaks with Input
To call peaks from a bigWig track with an input file, use the callPeaks_Input
command.
Option | Description | Default |
---|---|---|
file | BigWig track to analyse | |
-i, --input | Control input track to calculate significance of peaks | |
-t, --threshold | Threshold for selecting candidate peaks | 4 |
-w, --window | Window size for rolling mean to select candidate peaks | 400 |
-f, --folder | Output folder | "./" |
--skipheader | Skip writing the header | False |
Score a Bed file
To score the peaks in an existing Bed file, use the scoreBed
command.
Option | Description | Default |
---|---|---|
file | BigWig Track to analyse | |
-b, --bed | Bed file of regions to be scored | |
-f, --folder | Output folder | "./" |
--skipheader | Skip writing the header | False |
Examples
There is a basic bigWig file included in the test
subdirectory. To try out the caller, execute it on this file.
lanceotron callPeaks test/chr22.bw -f output_folder
Citation
@article {Hentges2021.01.25.428108,
author = {Hentges, Lance D. and Sergeant, Martin J. and Downes, Damien J. and Hughes, Jim R. and Taylor, Stephen},
title = {LanceOtron: a deep learning peak caller for ATAC-seq, ChIP-seq, and DNase-seq},
year = {2021},
doi = {10.1101/2021.01.25.428108},
publisher = {Cold Spring Harbor Laboratory},
URL = {https://www.biorxiv.org/content/early/2021/01/27/2021.01.25.428108},
journal = {bioRxiv}
}
Building the documentation
To serve the documentation locally, use
python -m mkdocs serve
Bug Reports and Improvement Suggestions
Please raise an issue if there is anything you wish to ask or contribute.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for lanceotron-1.0.8-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | e69193f6e51865e68784395eed273636a8c0623f1e192a37b1465b3b7d6577a8 |
|
MD5 | 29e2214db968eb1d170466c714405601 |
|
BLAKE2b-256 | 5e8ed747edb186573c038eaf4ba553a138738dba2278e6d0bc96d89891d3fb1a |