Evidence map›Paper›PMID 34056596›Full record

ArticleNAR genomics and bioinformatics2021

Polee: RNA-Seq analysis using approximate likelihood.

Daniel C Jones, Walter L Ruzzo

Open access · goldAbstract read
In one paragraph

Article in NAR genomics and bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 47% of its field
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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
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

2 authors at 1 institution in 1 country.

Daniel C JonesPaul G. Allen School of Computer Science & Engineering, University of Washington, Box 352350, Seattle, WA 98195-2350, USA.ORCID https://orcid.org/0000-0001-7055-3119
Walter L RuzzoPaul G. Allen School of Computer Science & Engineering, University of Washington, Box 352350, Seattle, WA 98195-2350, USA.
University of Washington · US

Funding

Pathological Mechanisms of Human Cerebeller MalformationsR01NS095733 · NINDS · SEATTLE CHILDREN'S HOSPITAL · PI MILLEN, KATHLEEN JOYCE · 2016 to 2020
$3.0M
NINDS NIH HHS R01 NS095733
6 · The paper itself

Abstract

The analysis of mRNA transcript abundance with RNA-Seq is a central tool in molecular biology research, but often analyses fail to account for the uncertainty in these estimates, which can be significant, especially when trying to disentangle isoforms or duplicated genes. Preserving uncertainty necessitates a full probabilistic model of the all the sequencing reads, which quickly becomes intractable, as experiments can consist of billions of reads. To overcome these limitations, we propose a new method of approximating the likelihood function of a sparse mixture model, using a technique we call the Pólya tree transformation. We demonstrate that substituting this approximation for the real thing achieves most of the benefits with a fraction of the computational costs, leading to more accurate detection of differential transcript expression and transcript coexpression.

Identifiers

PMID34056596
PMCPMC8152449
OpenAlexW3165336786

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.