MPRAscore: robust and non-parametric analysis of massively parallel reporter assays

Research output: Contribution to journalArticle

Abstract

MOTIVATION: Massively parallel reporter assays (MPRA) enable systematic screening of DNA sequence variants for effects on transcriptional activity. However, convenient analysis tools are still needed. RESULTS: We introduce MPRAscore, a novel tool to infer allele-specific effects on transcription from MPRA data. MPRAscore uses a weighted, variance-regularized method to calculate variant effect sizes robustly, and a permutation approach to test for significance without assuming normality or independence. AVAILABILITY AND IMPLEMENTATION: Source code (C++), precompiled binaries and data used in the paper at https://github.com/abhisheknrl/MPRAscore and https://www.ncbi.nlm.nih.gov/bioproject/PRJNA554195. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Details

Authors
Organisations
External organisations
  • Broad Institute
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Bioinformatics and Systems Biology
  • Medical Genetics
Original languageEnglish
Pages (from-to)5351-5353
Number of pages3
JournalBioinformatics (Oxford, England)
Volume35
Issue number24
Publication statusPublished - 2019 Dec 15
Publication categoryResearch
Peer-reviewedYes