Evidence map›Paper›PMID 32641141›Full record

ArticleGenome biology2020

Sierra: discovery of differential transcript usage from polyA-captured single-cell RNA-seq data.

Ralph Patrick, David T Humphreys, Vaibhao Janbandhu, Alicia Oshlack, Joshua W K Ho, Richard P Harvey, Kitty K Lo

Abstract readValidation Study
In one paragraph

Article in Genome biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 papers.

0numbers the graph read from it
0cells of the map it votes in
69citing 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

69 citing papers in PubMed.

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9 more citing papers are in PubMed but not listed here.

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

7 authors.

Ralph PatrickVictor Chang Cardiac Research Institute, 405 Liverpool St., Darlinghurst, 2010, Australia.
David T HumphreysVictor Chang Cardiac Research Institute, 405 Liverpool St., Darlinghurst, 2010, Australia.
Vaibhao JanbandhuVictor Chang Cardiac Research Institute, 405 Liverpool St., Darlinghurst, 2010, Australia.
Alicia OshlackMurdoch Children's Research Institute, Parkville, 3052, Victoria, Australia.
Joshua W K HoVictor Chang Cardiac Research Institute, 405 Liverpool St., Darlinghurst, 2010, Australia.
Richard P HarveyVictor Chang Cardiac Research Institute, 405 Liverpool St., Darlinghurst, 2010, Australia. r.harvey@victorchang.edu.au.
Kitty K LoSchool of Mathematics and Statistics, Faculty of Science, The University of Sydney, Camperdown, 2006, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High-throughput single-cell RNA-seq (scRNA-seq) is a powerful tool for studying gene expression in single cells. Most current scRNA-seq bioinformatics tools focus on analysing overall expression levels, largely ignoring alternative mRNA isoform expression. We present a computational pipeline, Sierra, that readily detects differential transcript usage from data generated by commonly used polyA-captured scRNA-seq technology. We validate Sierra by comparing cardiac scRNA-seq cell types to bulk RNA-seq of matched populations, finding significant overlap in differential transcripts. Sierra detects differential transcript usage across human peripheral blood mononuclear cells and the Tabula Muris, and 3

Indexed as

3' Untranslated RegionsGene Expression RegulationSequence Analysis, RNASingle-Cell AnalysisSoftwareAnimalsHumansLeukocytes, MononuclearMiceMyocardiumPoly A3' Untranslated RegionsPoly AAlternative polyadenylationDifferential transcript usemRNA isoformsscRNA-seq

Identifiers

PMID32641141
PMCPMC7341584

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.