cover of episode tfboot: Bootstrapping and statistical analysis for transcription factor binding site-disrupting variants in gene sets

tfboot: Bootstrapping and statistical analysis for transcription factor binding site-disrupting variants in gene sets

2023/7/16
logo of podcast PaperPlayer biorxiv bioinformatics

PaperPlayer biorxiv bioinformatics

Frequently requested episodes will be transcribed first

Shownotes Transcript

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.07.14.549004v1?rss=1

Authors: Turner, S. D., Morrill, K., Gedman, G., Titus, A. J.

Abstract: Motivation: Genetic variants in noncoding regions can drive changes in phenotype disrupting transcription factor binding site (TFBS) motifs. Other tools including motifbreakR have been developed to assess the impact of TFBS-disrupting variants. Here we introduce the tfboot package for statistically evaluating the TFBS disruption across a set of variants in upstream promoter regions. Results: The tfboot package builds on motifbreakR, plyranges, and GenomicRanges to provide methods for bootstrapping TFBS disruption to statistically quantify the impact across gene sets of interest compared to an empirical null distribution. We demonstrate the analysis here on variants in the elephant genome. The tfboot package readily integrates with Bioconductor and tidyverse-based workflows. Availability: The tfboot package is implemented as an R package and is released under the MIT license at https://github.com/colossal-compsci/tfboot.

Copy rights belong to original authors. Visit the link for more info

Podcast created by Paper Player, LLC