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An integrative toolkit for detecting cell type-specific regulators

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Documentation Status pypi license


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.



Sun H, Wang J, Gong Z, Yao J, Wang Y, Xu J, Yuan GC, Zhang Y, Shao Z. Quantitative integration of epigenomic variation and transcription factor binding using MAmotif toolkit identifies an important role of IRF2 as transcription activator at gene promoters. Cell discovery. 2018 Jul 10;4(1):38.


The latest release of MAmotif is available at PyPI:

$ pip install mamotif

Or you can install MAmotif via conda:

$ conda install -c bioconda mamotif


To see the full documentation of MAmotif, please refer to:


BSD 3-Clause License

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