Evidence map›Paper›PMID 19043412›Full record

ArticleNature methods2009

High-resolution mapping of copy-number alterations with massively parallel sequencing.

Derek Y Chiang, Gad Getz, David B Jaffe, Michael J T O'Kelly, Xiaojun Zhao, Scott L Carter, Carsten Russ, Chad Nusbaum, Matthew Meyerson, Eric S Lander

Abstract read
In one paragraph

Article in Nature methods, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 282 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
282citing 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

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

  1. Pooled it
  2. Trial
  3. Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. The reckoning of chromosomal instability: past, present, future.Chromosome research : an international journal on the molecular, supramolecular and evolutionary aspects of chromosome biology · 2024
    Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Whole genome sequencing-based copy number variations reveal novel pathways and targets in Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2022
    Article
  17. Article
  18. Identification of Copy Number Alterations from Next-Generation Sequencing Data.Advances in experimental medicine and biology · 2022
    Article
  19. Article
  20. Article

222 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

10 authors.

Derek Y ChiangBroad Institute, Massachusetts Institute of Technology, 7 Cambridge Center, Cambridge, MA 02142, USA.
Gad Getz
David B Jaffe
Michael J T O'Kelly
Xiaojun Zhao
Scott L Carter
Carsten Russ
Chad Nusbaum
Matthew Meyerson
Eric S Lander

Funding

Large Scale Sequencing and Analysis of GenomesU54HG003067 · NHGRI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI GABRIEL, STACEY, LANDER, ERIC S · 2004 to 2015
$568.6M
Center for Cancer Genome CharacterizationU24CA126546 · NCI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI MEYERSON, MATTHEW L. · 2006 to 2009
$7.7M
TOOLS FOR HIGH RESOLUTION LINKAGE MAPPING OF HUMAN GENESR01HG000367 · NHGRI · UNIVERSITY OF UTAH · PI WHITE, RAYMOND L · 1990 to 1992
–
NCI NIH HHS 5U24 CA 126546NCI NIH HHS U24 CA126546NHGRI NIH HHS 5U54 HG 00367NHGRI NIH HHS U54 HG003067
6 · The paper itself

Abstract

Cancer results from somatic alterations in key genes, including point mutations, copy-number alterations and structural rearrangements. A powerful way to discover cancer-causing genes is to identify genomic regions that show recurrent copy-number alterations (gains and losses) in tumor genomes. Recent advances in sequencing technologies suggest that massively parallel sequencing may provide a feasible alternative to DNA microarrays for detecting copy-number alterations. Here we present: (i) a statistical analysis of the power to detect copy-number alterations of a given size; (ii) SegSeq, an algorithm to segment equal copy numbers from massively parallel sequence data; and (iii) analysis of experimental data from three matched pairs of tumor and normal cell lines. We show that a collection of approximately 14 million aligned sequence reads from human cell lines has comparable power to detect events as the current generation of DNA microarrays and has over twofold better precision for localizing breakpoints (typically, to within approximately 1 kilobase).

Indexed as

Databases, GeneticAlgorithmsBase SequenceCell Line, TumorChromosomes, HumanGene DosageHumans

Identifiers

PMID19043412
PMCPMC2630795

What OpenQuestion holds

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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.