PT  - JOURNAL ARTICLE
AU  - Soumen Khan
AU  - Abhik Bhattacharjee
AU  - Pranav Badhe
AU  - Chinmay Dongaonkar
AU  - Yash Gaglani
TI  - Motifizer: a tool for parsing high-throughput sequencing datasets and quantitative comparative analyses of transcription factor-binding sites
AID  - 10.1101/2022.04.03.486862
DP  - 2022 Jan 01
TA  - bioRxiv
PG  - 2022.04.03.486862
4099  - http://biorxiv.org/content/early/2022/04/05/2022.04.03.486862.short
4100  - http://biorxiv.org/content/early/2022/04/05/2022.04.03.486862.full
AB  - 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 StatementThe authors have declared no competing interest.