Evidence map›Paper›PMID 24814956›Full record

ArticleThe Journal of molecular diagnostics : JMD2014

cDNA hybrid capture improves transcriptome analysis on low-input and archived samples.

Christopher R Cabanski, Vincent Magrini, Malachi Griffith, Obi L Griffith, Sean McGrath, Jin Zhang, Jason Walker, Amy Ly, Ryan Demeter, Robert S Fulton and 5 more

Open access · hybridAbstract read
In one paragraph

Article in The Journal of molecular diagnostics : JMD, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
3.4field-weighted citation impact, top 7% 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

28 citing papers in PubMed, 47 citations in OpenAlex.

  1. Trial
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  6. Article
  7. From bulk, single-cell to spatial RNA sequencing.International journal of oral science · 2021
    Review
  8. Article
  9. Article
  10. Review
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Review
  17. Breast Cancer Neoantigens Can Induce CD8Cancer immunology research · 2017
    Article
  18. Article
  19. Review
  20. Gut microbiota, metabolites and host immunity.Nature reviews. Immunology · 2016
    Review
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

15 authors at 1 institution in 1 country.

Christopher R CabanskiThe Genome Institute, Washington University School of Medicine, St. Louis, Missouri; Division of Oncology, Department of Internal Medicine, Washington University School of Medicine, St. Louis, Missouri.
Vincent MagriniThe Genome Institute, Washington University School of Medicine, St. Louis, Missouri; Department of Genetics, Washington University School of Medicine, St. Louis, Missouri.
Malachi GriffithThe Genome Institute, Washington University School of Medicine, St. Louis, Missouri; Department of Genetics, Washington University School of Medicine, St. Louis, Missouri.
Obi L GriffithThe Genome Institute, Washington University School of Medicine, St. Louis, Missouri; Division of Oncology, Department of Internal Medicine, Washington University School of Medicine, St. Louis, Missouri.
Sean McGrathThe Genome Institute, Washington University School of Medicine, St. Louis, Missouri.
Jin ZhangThe Genome Institute, Washington University School of Medicine, St. Louis, Missouri; Division of Oncology, Department of Internal Medicine, Washington University School of Medicine, St. Louis, Missouri.
Jason WalkerThe Genome Institute, Washington University School of Medicine, St. Louis, Missouri.
Amy LyThe Genome Institute, Washington University School of Medicine, St. Louis, Missouri.
Ryan DemeterThe Genome Institute, Washington University School of Medicine, St. Louis, Missouri.
Robert S FultonThe Genome Institute, Washington University School of Medicine, St. Louis, Missouri.
Winnie W PongDepartment of Neurology, Washington University School of Medicine, St. Louis, Missouri.
David H GutmannDepartment of Neurology, Washington University School of Medicine, St. Louis, Missouri; Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, Missouri.
Ramaswamy GovindanThe Genome Institute, Washington University School of Medicine, St. Louis, Missouri; Division of Oncology, Department of Internal Medicine, Washington University School of Medicine, St. Louis, Missouri.
Elaine R MardisThe Genome Institute, Washington University School of Medicine, St. Louis, Missouri; Department of Genetics, Washington University School of Medicine, St. Louis, Missouri; Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, Missouri.
Christopher A MaherThe Genome Institute, Washington University School of Medicine, St. Louis, Missouri; Division of Oncology, Department of Internal Medicine, Washington University School of Medicine, St. Louis, Missouri; Alvin J. Siteman Cancer Center, Washington University School of Medicine, St. Louis, Missouri; Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, Missouri. Electronic address: cmaher@dom.wustl.edu.
Washington University in St. Louis · US

Funding

Large Scale Genome SequencingU54HG003079 · NHGRI · WASHINGTON UNIVERSITY · PI DUTCHER, SUSAN K · 2004 to 2016
$445.7M
Characterization of Cancer Transcriptomes using Next Generation SequencingR00CA149182 · NCI · WASHINGTON UNIVERSITY · PI MAHER, CHRISTOPHER A · 2011 to 2013
$685k
NCI NIH HHS R00 CA149182NHGRI NIH HHS U54 HG003079
6 · The paper itself

Abstract

The use of massively parallel sequencing for studying RNA expression has greatly enhanced our understanding of the transcriptome through the myriad ways these data can be characterized. In particular, clinical samples provide important insights about RNA expression in health and disease, yet these studies can be complicated by RNA degradation that results from the use of formalin as a clinical preservative and by the limited amounts of RNA often available from these precious samples. In this study we describe the combined use of RNA sequencing with an exome capture selection step to enhance the yield of on-exon sequencing read data when compared with RNA sequencing alone. In particular, the exome capture step preserves the dynamic range of expression, permitting differential comparisons and validation of expressed mutations from limited and FFPE preserved samples, while reducing the data generation requirement. We conclude that cDNA hybrid capture has the potential to significantly improve transcriptome analysis from low-yield FFPE material.

Indexed as

ExomeAdenocarcinomaAdenocarcinoma of LungDNA, ComplementaryGene Expression ProfilingGene FusionHumansLung NeoplasmsRNASequence Analysis, RNADNA, ComplementaryRNA

Identifiers

PMID24814956
PMCPMC4078367
OpenAlexW2128212390

What OpenQuestion holds

Textmetadata
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.