Evidence map›Paper›PMID 36759904›Full record

ArticleGenome biology2023

REPAC: analysis of alternative polyadenylation from RNA-sequencing data.

Eddie L Imada, Christopher Wilks, Ben Langmead, Luigi Marchionni

Abstract read
In one paragraph

Article in Genome biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Eddie L ImadaDepartment of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, USA. eimada@med.cornell.edu.ORCID 0000-0001-9527-3703
Christopher WilksDepartment of Computer Science, Johns Hopkins University, Baltimore, USA.
Ben LangmeadDepartment of Computer Science, Johns Hopkins University, Baltimore, USA.
Luigi MarchionniDepartment of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, USA. marchion@med.cornell.edu.

Funding

Weill Cornell Medicine (WCM) SPORE in Prostate CancerP50CA211024 · NCI · WEILL MEDICAL COLL OF CORNELL UNIV · PI GUDAS, LORRAINE J · 2017 to 2021
$10.9M
Methods for sequencing data analysis and archive-scale data science - RenewalR35GM139602 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI Benjamin Thomas Langmead · 2021 to 2026
$5.0M
Analysis of genomics datasets at a massive scaleR01GM121459 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI HANSEN, KASPER DANIEL · 2017 to 2021
$2.3M
Hardening and Scaling Core Genomics SoftwareR01GM118568 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI LANGMEAD, BENJAMIN THOMAS · 2016 to 2020
$2.0M
Hardwiring Mechanism into Predicting Cancer Phenotypes by Computational LearningR01CA200859 · NCI · WEILL MEDICAL COLL OF CORNELL UNIV · PI MARCHIONNI, LUIGI · 2016 to 2020
$1.9M
NCI NIH HHS P50 CA211024NCI NIH HHS R01 CA200859NIGMS NIH HHS R01 GM118568NIGMS NIH HHS R01 GM121459NIGMS NIH HHS R35 GM139602
6 · The paper itself

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.

Indexed as

High-Throughput Nucleotide SequencingPolyadenylation3' Untranslated RegionsRNA, MessengerSequence Analysis, RNA3' Untranslated RegionsRNA, MessengerCompositionsMethodPolyadenylation

Identifiers

PMID36759904
PMCPMC9912678

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.