Title | REPAC: analysis of alternative polyadenylation from RNA-sequencing data. |
Publication Type | Journal Article |
Year of Publication | 2023 |
Authors | Imada EL, Wilks C, Langmead B, Marchionni L |
Journal | Genome Biol |
Volume | 24 |
Issue | 1 |
Pagination | 22 |
Date Published | 2023 Feb 09 |
ISSN | 1474-760X |
Keywords | 3' Untranslated Regions, High-Throughput Nucleotide Sequencing, Polyadenylation, RNA, Messenger, Sequence Analysis, RNA |
Abstract | Alternative polyadenylation (APA) is an important post-transcriptional mechanism that has major implications in biological processes and diseases. Although specialized sequencing methods for polyadenylation exist, availability of these data are limited compared to RNA-sequencing data. We developed REPAC, a framework for the analysis of APA from RNA-sequencing data. Using REPAC, we investigate the landscape of APA caused by activation of B cells. We also show that REPAC is faster than alternative methods by at least 7-fold and that it scales well to hundreds of samples. Overall, the REPAC method offers an accurate, easy, and convenient solution for the exploration of APA. |
DOI | 10.1186/s13059-023-02865-5 |
Alternate Journal | Genome Biol |
PubMed ID | 36759904 |
PubMed Central ID | PMC9912678 |
Grant List | R01 CA200859 / CA / NCI NIH HHS / United States R01 GM121459 / GM / NIGMS NIH HHS / United States R35 GM139602 / GM / NIGMS NIH HHS / United States P50 CA211024 / CA / NCI NIH HHS / United States R01 GM118568 / GM / NIGMS NIH HHS / United States |
Related Faculty:
Eddie Luidy Imada, Ph.D. Luigi Marchionni, M.D., Ph.D.