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An integrative toolkit for detecting cell type-specific regulators

Project description

Documentation Status pypi license

Introduction

MAmotif is used to compare two ChIP-seq samples of the same protein from different cell types or conditions (e.g. Mutant vs Wild-type) and identify transcriptional factors (TFs) associated with the cell-type biased binding of this protein as its co-factors, by using TF binding information obtained from motif analysis (or from other ChIP-seq data).

MAmotif automatically combines MAnorm model to perform quantitative comparison on given ChIP-seq samples together with Motif-Scan toolkit to scan ChIP-seq peaks for TF binding motifs, and uses a systematic integrative analysis to search for TFs whose binding sites are significantly associated with the cell-type biased peaks between two ChIP-seq samples.

When applying to ChIP-seq data of histone marks of regulatory elements (such as H3K4me3 for active promoters and H3K9/27ac for active promoter/enhancers), or DNase/ATAC-seq data, MAmotif can be used to detect cell-type specific regulators.

Workflow

https://github.com/shao-lab/MAmotif/blob/master/docs/source/image/MAmotif_workflow.png

Installation

The latest release of MAmotif is available at PyPI:

$ pip install mamotif

Or you can install MAmotif via conda:

$ conda install -c bioconda mamotif

Documentation

To see the full documentation of MAmotif, please refer to: http://mamotif.readthedocs.io/en/latest/

Project details


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