Evidence map›Paper›PMID 24583115›Full record

ArticleMethods (San Diego, Calif.)2014

Integrative analysis of many RNA-seq datasets to study alternative splicing.

Wenyuan Li, Chao Dai, Shuli Kang, Xianghong Jasmine Zhou

Abstract read
In one paragraph

Article in Methods (San Diego, Calif.), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Characterization of uniqueOncotarget · 2020
    Article
  3. Article
  4. Bioinformatics challenges and perspectives when studying the effect of epigenetic modifications on alternative splicing.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2018
    Review
  5. Article
  6. The determinants of alternative RNA splicing in human cells.Molecular genetics and genomics : MGG · 2017
    Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Review
  12. Article
  13. Article
  14. Advanced Applications of RNA Sequencing and Challenges.Bioinformatics and biology insights · 2015
    Review
  15. 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

4 authors.

Wenyuan LiMolecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA.
Chao DaiMolecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA.
Shuli KangMolecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA.
Xianghong Jasmine ZhouMolecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA. Electronic address: xjzhou@usc.edu.

Funding

MAPGen Knowledge Base (MAPGenKB) and Coordination CenterU01HL108634 · NHLBI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI ZHOU, XIANGHONG JASMINE · 2011 to 2015
$5.3M
Integrative Analysis of Public RNA-seq RepositoriesR01GM105431 · NIGMS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI ZHOU, XIANGHONG JASMINE · 2013 to 2016
$1.3M
NHLBI NIH HHS U01 HL108634NHLBI NIH HHS U01HL108634NIGMS NIH HHS R01 GM105431NIGMS NIH HHS R01GM105431
6 · The paper itself

Abstract

Alternative splicing is an important gene regulatory mechanism that dramatically increases the complexity of the proteome. However, how alternative splicing is regulated and how transcription and splicing are coordinated are still poorly understood, and functions of transcript isoforms have been studied only in a few limited cases. Nowadays, RNA-seq technology provides an exceptional opportunity to study alternative splicing on genome-wide scales and in an unbiased manner. With the rapid accumulation of data in public repositories, new challenges arise from the urgent need to effectively integrate many different RNA-seq datasets for study alterative splicing. This paper discusses a set of advanced computational methods that can integrate and analyze many RNA-seq datasets to systematically identify splicing modules, unravel the coupling of transcription and splicing, and predict the functions of splicing isoforms on a genome-wide scale.

Indexed as

Alternative SplicingComputational BiologyData Interpretation, StatisticalDatasets as TopicSequence Analysis, RNAAlternative splicingIntegrative analysisRNA-seq data

Identifiers

PMID24583115
PMCPMC4120771

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.