IMPALA: A Comprehensive Pipeline for Detecting and Elucidating Mechanisms of Allele Specific Expression in Cancer

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Abstract Summary Allele-specific expression (ASE), where transcripts from one allele are more abundant than transcripts from the other, can arise from various genetic mechanisms and has implications for gene regulation and disease. We present IMPALA (Integrated Mapping and Profiling of Allelically-expressed Loci with Annotations), a versioned and containerized pipeline for detecting ASE in samples including cancer genomes. IMPALA leverages RNA sequencing data and, optionally, phased variant, copy number variant (CNV), allelic methylation, and mutation data to identify ASE genes and uncover underlying regulatory mechanisms. IMPALA incorporates the MBASED framework for ASE detection, and outputs a comprehensive summary table and informative figures to visualize the genomic distribution of ASE genes and their correlation with potential regulatory causes. We applied IMPALA to a cancer sample and identified thousands of genes with ASE and highlighted potential somatic events that may have influenced ASE of these genes. ASE data can be used to detect the downstream consequences of genomic alterations, which facilitates the identification of dysregulated cancer-related genes. IMPALA thus provides researchers with a powerful tool for both ASE analysis and for investigating genetic factors correlated with ASE. Availability and implementation IMPALA is licensed under GNU General Public License v3.0 and freely available at https://github.com/bcgsc/IMPALA and https://doi.org/10.5281/zenodo.8019168 with documentation and tutorial. Contact sjones@bcgsc.ca Supplemental information Supplemental materials are available at Bioinformatics online. Issue section: Gene expression

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