QuASAR-MPRA: accurate allele-specific analysis for massively parallel reporter assays
Author(s) -
Cynthia A. Kalita,
Gregory A. Moyerbrailean,
Andrew Brown,
Xiaoquan Wen,
Francesca Luca,
Roger Piqué-Regi
Publication year - 2017
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btx598
Subject(s) - biology , computational biology , enhancer , replicate , genetics , allele , gene , genome , computer science , gene expression , statistics , mathematics
The majority of the human genome is composed of non-coding regions containing regulatory elements such as enhancers, which are crucial for controlling gene expression. Many variants associated with complex traits are in these regions, and may disrupt gene regulatory sequences. Consequently, it is important to not only identify true enhancers but also to test if a variant within an enhancer affects gene regulation. Recently, allele-specific analysis in high-throughput reporter assays, such as massively parallel reporter assays (MPRAs), have been used to functionally validate non-coding variants. However, we are still missing high-quality and robust data analysis tools for these datasets.
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