Evidence map›Paper›PMID 26813401›Full record

ReviewGenome biology2016

A survey of best practices for RNA-seq data analysis.

Ana Conesa, Pedro Madrigal, Sonia Tarazona, David Gomez-Cabrero, Alejandra Cervera, Andrew McPherson, Michał Wojciech Szcześniak, Daniel J Gaffney, Laura L Elo, Xuegong Zhang and 1 more

Erratum issuedAbstract readReview
In one paragraph

Review in Genome biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1,447 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1,447citing papers in PubMed, 1 pooled it
–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

1,447 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Integrated Transcriptomic Analysis of Skin Pigmentation Development inInternational journal of molecular sciences · 2026
    Article
  8. Article
  9. Article
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  14. Article
  15. Review
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  18. Article
  19. Effects of Fertilizer Rates on Growth ofLife (Basel, Switzerland) · 2026
    Article
  20. Article

1,387 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Ana ConesaInstitute for Food and Agricultural Sciences, Department of Microbiology and Cell Science, University of Florida, Gainesville, FL, 32603, USA. aconesa@ufl.edu.
Pedro MadrigalWellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK. pm12@sanger.ac.uk.
Sonia TarazonaCentro de Investigación Príncipe Felipe, Genomics of Gene Expression Laboratory, 46012, Valencia, Spain.
David Gomez-CabreroUnit of Computational Medicine, Department of Medicine, Karolinska Institutet, Karolinska University Hospital, 171 77, Stockholm, Sweden.
Alejandra CerveraSystems Biology Laboratory, Institute of Biomedicine and Genome-Scale Biology Research Program, University of Helsinki, 00014, Helsinki, Finland.
Andrew McPhersonSchool of Computing Science, Simon Fraser University, Burnaby, V5A 1S6, BC, Canada.
Michał Wojciech SzcześniakDepartment of Bioinformatics, Institute of Molecular Biology and Biotechnology, Adam Mickiewicz University in Poznań, 61-614, Poznań, Poland.
Daniel J GaffneyWellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK.
Laura L EloTurku Centre for Biotechnology, University of Turku and Åbo Akademi University, FI-20520, Turku, Finland.
Xuegong ZhangKey Lab of Bioinformatics/Bioinformatics Division, TNLIST and Department of Automation, Tsinghua University, Beijing, 100084, China.
Ali MortazaviDepartment of Developmental and Cell Biology, University of California, Irvine, Irvine, CA, 92697-2300, USA. ali.mortazavi@uci.edu.

Funding

Comparative analysis of the 4D encoding of regulatory networks in stem cellsDP2GM111100 · NIGMS · UNIVERSITY OF CALIFORNIA-IRVINE · PI MORTAZAVI, SEYED ALI · 2013 to 2013
$2.3M
Medical Research Council MC_PC_12009NIGMS NIH HHS DP2 GM111100Wellcome Trust
6 · The paper itself

Abstract

RNA-sequencing (RNA-seq) has a wide variety of applications, but no single analysis pipeline can be used in all cases. We review all of the major steps in RNA-seq data analysis, including experimental design, quality control, read alignment, quantification of gene and transcript levels, visualization, differential gene expression, alternative splicing, functional analysis, gene fusion detection and eQTL mapping. We highlight the challenges associated with each step. We discuss the analysis of small RNAs and the integration of RNA-seq with other functional genomics techniques. Finally, we discuss the outlook for novel technologies that are changing the state of the art in transcriptomics.

Indexed as

GenomicsAlternative SplicingBase SequenceGene Expression ProfilingGene FusionHigh-Throughput Nucleotide SequencingRNASequence Analysis, RNASoftwareRNA

Identifiers

PMID26813401
PMCPMC4728800

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.