MPRAscore : robust and non-parametric analysis of massively parallel reporter assays
(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.
(Less)
- author
- Niroula, Abhishek LU ; Ajore, Ram LU and Nilsson, Björn LU
- organization
- publishing date
- 2019-12-15
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Bioinformatics
- volume
- 35
- issue
- 24
- pages
- 3 pages
- publisher
- Oxford University Press
- external identifiers
-
- pmid:31359027
- scopus:85077774150
- 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
- 2024-08-22 14:39:37
@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}}, }