henhaobio
Sign in

bioRxivBioinformaticsPreprint

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

Stephen TurneriD, Kathleen M. MorrilliD, Gregory L. GedmaniD, Alexander TitusiD

PDFDOICode

Abstract

MotivationGenetic 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. ResultsThe 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. AvailabilityThe tfboot package is implemented as an R package and is released under the MIT license at https://github.com/colossal-compsci/tfboot.

Citations
0

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISSantana-Gar '19Lin '26Shen '20Ouyang '22Eickhardt '16Roskams-Hie '26
55% semantic matchBioinformatics
Walter Santana-Garcia, Maria Rocha-Acevedo, Lucia Ramirez-Navarro+6 more·Computational and Structural Biotechnology Journal·Jan 1, 2019· 15 citations