Skip to main content

DNase-seq analysis library

Project description

https://travis-ci.org/jpiper/pyDNase.svg?branch=master https://coveralls.io/repos/jpiper/pyDNase/badge.svg?branch=master&service=github

Introduction

pyDNase is a suite of tools for analysing DNase-seq data - pyDNase comes with several analysis scripts covering several common use cases of DNase-seq analysis, and also an implementation of the Wellington, Wellington 1D, and Wellington-boostrap footprinting algorithms.

An easy-to-understand DNase-seq footprinting tutorial can be found here and full documentation can be accessed here

API

Many people currently analyzing DNase-seq data are using tools designed for ChIP-seq work, but may be inappropriate for DNase-seq data where one is less interested in the overlaps of sequenced fragments, but the site at which the cut occurs (the 5’ most end of the aligned sequence fragment).

pyDNase has an underlying API to interface with a sorted and indexed BAM file from a DNase-seq experiment, allowing efficient and easy random access of DNase-seq cut data from any genomic location, e.g.

>>> import pyDNase
>>> reads = pyDNase.BAMHandler(pyDNase.example_reads())
>>> reads["chr6,170863500,170863532,+"]
{'+': [0,0,0,1,0,0,1,1,2,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1,0,0,1,1,0,0,0,1],
 '-': [0,10,1,0,1,0,4,9,0,1,0,2,1,0,0,0,0,0,3,0,6,3,0,0,0,1,1,1,3,0,3,6]}

Querying the BAMHandler object returns a dictionary containing lists with DNase cut counts on the positive reference strand (+), and cuts on the negative reference strand (-). pyDNase efficiently caches the cut data queried, so that multiple requests from the same genomic locations do not require repeated lookups from the BAM file (this can be disabled). See the full documentation for full details.

Installation

to install pyDNase, run:

$ pip install pyDNase

for full documentation go to: http://pythonhosted.org/pyDNase/

Support

If you’re having any troubles, please send an email to j.piper@me.com and I’ll do my best to help you out. If you notice any bugs, then please raise an issue over at the github repo. If you require more formal training on the analysis of DNase-seq or ATAC-seq data, I am available for consultancy. Likewise, if you are a commercial entity looking for a support contract, please get in touch.

Contributions

I highly encourage contributions! This is my first software development project - send any pull requests this way. I’m particularly interested in cool analysis scripts that anyone has written.

Reference

License

Copyright (C) 2015 Jason Piper. This work is licensed under the MIT license, see LICENCE.TXT for details. If you require the use of this software under a difference license, please email me at j.piper@me.com.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pyDNase-0.3.0.tar.gz (339.7 kB view details)

Uploaded Source

File details

Details for the file pyDNase-0.3.0.tar.gz.

File metadata

  • Download URL: pyDNase-0.3.0.tar.gz
  • Upload date:
  • Size: 339.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for pyDNase-0.3.0.tar.gz
Algorithm Hash digest
SHA256 dba03cadca37929a1cc41545e962136f29efc41f8e3c6de042c51c47ee04d558
MD5 0c91faebb3ea454a1f53d06d3442d9f5
BLAKE2b-256 c0f93210706f883579df6f52efa5c6ec33c66edb043f477ae508987dc4041f50

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page