FindIT2: an R/Bioconductor package to identify influential transcription factor and targets based on multi-omics data

Background: Transcription factors (TFs) play central roles in regulating gene expression. With the rapid growth in the use of high-throughput sequencing methods, there is a need to develop a comprehensive data processing and analyzing framework for inferring influential TFs based on ChIP-seq/ATAC-seq datasets. Results: Here, we introduce FindIT2 (Find Influential TFs and Targets), an R/Bioconductor package for annotating and processing high-throughput multi-omics data. FindIT2 supports a complete framework for annotating ChIP-seq/ ATAC-seq peaks, identifying TF targets by the combination of ChIP-seq and RNA-seq datasets, and inferring influential TFs based on different types of data input. Moreover, benefited from the annotation framework based on Bioconductor, FindIT2 can be applied to any species with genomic annotations, which is particularly useful for the non-model species that are less well-studied. Conclusion: FindIT2 provides a user-friendly and flexible framework to generate results at different levels according to the richness of the annotation information of user's species. FindIT2 is compatible with all the operating systems and is released under Artistic-2.0 License. The source code and documents are freely available through Bioconductor (https://bioconductor.org/packages/devel/bioc/html/FindIT2.html).

Automated summary

In this study, we introduce FindIT2, a software package that can process and analyze multi-omics data to infer influential transcription factors using ChIP-seq/ATAC-seq datasets. The package annotates ChIP-seq/ATAC-seq peaks, identifies transcription factor targets by combining ChIP-seq and RNA-seq data, and supports inference of influential transcription factors based on different types of data input. Moreover, FindIT2 is compatible with any species with genomic annotations, making it particularly useful for less well-studied non-model species.