Protocol for identifying functional regulatory mutation blocks by integrating genome sequencing and transcriptome data

Identifying functional mutation blocks (FMBs) that contribute to genome-wide transcriptional regulation remains a challenge. BayesPI-BAR version 3 (bpb3) is a Python-based tool for predicting FMBs by integrating DNA sequence data with gene expression data. Its application is demonstrated through four examples in two tasks: ranking transcription factors (TFs) most affected by 67 known single-nucleotide polymorphisms (SNPs) in regulatory regions and integrating the genomic distribution of SNPs with differential gene expression to identify FMBs that disrupt TF-DNA binding and gene expression in lymphoma. For complete details on the use and execution of this protocol, please refer to Yang et al. 1