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

Niroula, Abhishek LU ; Ajore, Ram LU and Nilsson, Björn LU (2019) In Bioinformatics 35(24). p.5351-5353
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:... (More)

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.

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author
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organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Bioinformatics
volume
35
issue
24
pages
3 pages
publisher
Oxford University Press
external identifiers
  • scopus:85077774150
  • pmid:31359027
ISSN
1367-4803
DOI
10.1093/bioinformatics/btz591
language
English
LU publication?
yes
id
b993c38d-478d-4625-bcd4-cba8b2e02216
date added to LUP
2020-01-29 13:01:41
date last changed
2024-05-29 07:57:20
@article{b993c38d-478d-4625-bcd4-cba8b2e02216,
  abstract     = {{<p>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.</p>}},
  author       = {{Niroula, Abhishek and Ajore, Ram and Nilsson, Björn}},
  issn         = {{1367-4803}},
  language     = {{eng}},
  month        = {{12}},
  number       = {{24}},
  pages        = {{5351--5353}},
  publisher    = {{Oxford University Press}},
  series       = {{Bioinformatics}},
  title        = {{MPRAscore : robust and non-parametric analysis of massively parallel reporter assays}},
  url          = {{http://dx.doi.org/10.1093/bioinformatics/btz591}},
  doi          = {{10.1093/bioinformatics/btz591}},
  volume       = {{35}},
  year         = {{2019}},
}