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Protocol for identifying functional regulatory mutation blocks by integrating genome sequencing and transcriptome
Mingyi Yang1, Gege Liu2, Magnar Bjørås3
1Department of Microbiology, Oslo University Hospital and University of Oslo, 0372 Oslo, Norway; Department of Medical Biochemistry, Oslo University Hospital and University of Oslo, 0372 Oslo, Norway.
None:
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.
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