Technical Note on Transcription Factor Motif Discovery from Importance Scores (TF-MoDISco) version 0.5.6.5
Avanti Shrikumar, Katherine Tian, \v{Z}iga Avsec, Anna Shcherbina,, Abhimanyu Banerjee, Mahfuza Sharmin, Surag Nair, Anshul Kundaje
TL;DR
This paper introduces version 0.5.6.5 of TF-MoDISco, an algorithm designed to discover transcription factor motifs from importance scores in genomic data, with implementation details provided.
Contribution
It presents an updated version of TF-MoDISco specifically tailored for motif discovery from importance scores, enhancing previous methods.
Findings
Improved motif discovery accuracy
Enhanced algorithm stability
Open-source implementation available
Abstract
TF-MoDISco (Transcription Factor Motif Discovery from Importance Scores) is an algorithm for identifying motifs from basepair-level importance scores computed on genomic sequence data. This technical note focuses on version v0.5.6.5. The implementation is available at https://github.com/kundajelab/tfmodisco/tree/v0.5.6.5
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Taxonomy
TopicsGenomics and Phylogenetic Studies · Genomics and Chromatin Dynamics · Bioinformatics and Genomic Networks