Evidence map›Paper›PMID 25870306›Full record

ArticleCold Spring Harbor protocols2015

RNA Sequencing and Analysis.

Kimberly R Kukurba, Stephen B Montgomery

Open access · bronzeAbstract read
In one paragraph

Article in Cold Spring Harbor protocols, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 415 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
415citing papers in PubMed, 4 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

415 citing papers in PubMed, 4 syntheses or guidelines pooled it, 911 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. Article

355 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

2 authors at 1 institution in 1 country.

Kimberly R KukurbaDepartment of Pathology, Stanford University School of Medicine, Stanford, California 94305; Department of Genetics, Stanford University School of Medicine, Stanford, California 94305;
Stephen B MontgomeryDepartment of Pathology, Stanford University School of Medicine, Stanford, California 94305; Department of Genetics, Stanford University School of Medicine, Stanford, California 94305; Department of Computer Science, Stanford University School of Medicine, Stanford, California 94305.
Stanford University · US

Funding

Predicting causal non-coding variants in a founder populationR01HG008150 · NHGRI · STANFORD UNIVERSITY · PI MONTGOMERY, STEPHEN · 2015 to 2017
$1.4M
NHGRI NIH HHS R01 HG008150
6 · The paper itself

Abstract

RNA sequencing (RNA-Seq) uses the capabilities of high-throughput sequencing methods to provide insight into the transcriptome of a cell. Compared to previous Sanger sequencing- and microarray-based methods, RNA-Seq provides far higher coverage and greater resolution of the dynamic nature of the transcriptome. Beyond quantifying gene expression, the data generated by RNA-Seq facilitate the discovery of novel transcripts, identification of alternatively spliced genes, and detection of allele-specific expression. Recent advances in the RNA-Seq workflow, from sample preparation to library construction to data analysis, have enabled researchers to further elucidate the functional complexity of the transcription. In addition to polyadenylated messenger RNA (mRNA) transcripts, RNA-Seq can be applied to investigate different populations of RNA, including total RNA, pre-mRNA, and noncoding RNA, such as microRNA and long ncRNA. This article provides an introduction to RNA-Seq methods, including applications, experimental design, and technical challenges.

Indexed as

Computational BiologyHigh-Throughput Nucleotide SequencingSequence AnalysisSequence Analysis, RNA

Identifiers

PMID25870306
PMCPMC4863231
OpenAlexW2177784250

What OpenQuestion holds

Textmetadata
LicenceTDM
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.