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

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Bibtex

@article{b993c38d478d4625bcd4cba8b2e02216,
title = "MPRAscore: robust and non-parametric analysis of massively parallel reporter assays",
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.",
author = "Abhishek Niroula and Ram Ajore and Bj{\"o}rn Nilsson",
year = "2019",
month = dec,
day = "15",
doi = "10.1093/bioinformatics/btz591",
language = "English",
volume = "35",
pages = "5351--5353",
journal = "Bioinformatics",
issn = "1367-4803",
publisher = "Oxford University Press",
number = "24",

}