Plate IV.339 · Publications
MPRAnalyze: statistical framework for massively parallel reporter assays
Article in Genome Biology, 2 September 2019.
Abstract
Massively parallel reporter assays (MPRAs) can measure the regulatory function of thousands of DNA sequences in a single experiment. Despite growing popularity, MPRA studies are limited by a lack of a unified framework for analyzing the resulting data. Here we present MPRAnalyze: a statistical framework for analyzing MPRA count data. Our model leverages the unique structure of MPRA data to quantify the function of regulatory sequences, compare sequences' activity across different conditions, and provide necessary flexibility in an evolving field. We demonstrate the accuracy and applicability of MPRAnalyze on simulated and published data and compare it with existing methods.
Versions2
- PublishedGenome Biology10.1186/s13059-019-1787-z
- PreprintbioRxiv10.1101/527887
Cite
@article{ashuach2019mpranalyze,
title = {{MPRAnalyze: statistical framework for massively parallel reporter assays}},
author = {Ashuach, Tal and Fischer, David S. and Kreimer, Anat and Ahituv, Nadav and Theis, Fabian J. and Yosef, Nir},
journal = {Genome Biology},
publisher = {Springer Science and Business Media LLC},
year = {2019},
month = sep,
doi = {10.1186/s13059-019-1787-z},
url = {https://doi.org/10.1186/s13059-019-1787-z},
pmid = {31477158},
pmcid = {PMC6717970}
}