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Motifizer: a tool for parsing high-throughput sequencing datasets and quantitative comparative analyses of transcription factor-binding sites

View ORCID ProfileSoumen Khan, Abhik Bhattacharjee, Pranav Badhe, Chinmay Dongaonkar, Yash Gaglani
doi: https://doi.org/10.1101/2022.04.03.486862
Soumen Khan
1Indian Institute of Science Education and Research, Pune
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  • For correspondence: soumen.khan@students.iiserpune.ac.in
Abhik Bhattacharjee
2Maharashtra Institute of Technology, Pune
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Pranav Badhe
2Maharashtra Institute of Technology, Pune
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Chinmay Dongaonkar
2Maharashtra Institute of Technology, Pune
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Yash Gaglani
2Maharashtra Institute of Technology, Pune
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Abstract

Background Comparative analysis of Chromatin immunoprecipitation followed by massively parallel sequencing (ChIP-seq), combined with transcriptomics data (RNA-seq), can provide critical insights into gene regulatory networks controlled by transcription factors in a given biological context. While multiple programs exist, which need to be individually installed and executed to generate such information, a user-friendly tool with low system requirements which combines the various computational processes into one package, using a docker container, is lacking.

Results In this study, we present a user-interactive, infrastructure-independent computational pipeline, called Motifizer, which uses open source tools for processing ChIP-Seq and RNA-seq datasets. Motifizer performs extensive analysis of raw input data, performing peak calling, de-novo motif analysis and differential gene expression analysis on ChIP and RNA-seq datasets. Additionally, Motifizer can be used for analysis and quantitative comparison of transcription factor binding sites in user defined genomic regions. Motifizer also allows easy addition and/or changes of parameters, thereby adding to the versatility of the tool.

Conclusion The Motifizer tool is an easy to use tool which uses a docker container system to install and execute ChIP-seq and RNA-seq data parsing. The Analysis module of Motifizer can be employed to identify putative targets involved in gene regulatory networks. Motifizer can be accessed by a large user base and does not require programming skill by the user. Motifizer can be locally installed from the repository (https://github.com/abhikbhattacharjee/Motifizer)

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted April 05, 2022.
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Motifizer: a tool for parsing high-throughput sequencing datasets and quantitative comparative analyses of transcription factor-binding sites
Soumen Khan, Abhik Bhattacharjee, Pranav Badhe, Chinmay Dongaonkar, Yash Gaglani
bioRxiv 2022.04.03.486862; doi: https://doi.org/10.1101/2022.04.03.486862
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Motifizer: a tool for parsing high-throughput sequencing datasets and quantitative comparative analyses of transcription factor-binding sites
Soumen Khan, Abhik Bhattacharjee, Pranav Badhe, Chinmay Dongaonkar, Yash Gaglani
bioRxiv 2022.04.03.486862; doi: https://doi.org/10.1101/2022.04.03.486862

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