Evidence map›Paper›PMID 23028187›Full record

ArticleGenome research2013

Haplotype-based profiling of subtle allelic imbalance with SNP arrays.

Selina Vattathil, Paul Scheet

Abstract read
In one paragraph

Article in Genome research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Driver Mutations in Normal Airway Epithelium Elucidate Spatiotemporal Resolution of Lung Cancer.American journal of respiratory and critical care medicine · 2019
    Article
  18. Article
  19. Article
  20. 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

2 authors.

Selina VattathilHuman & Molecular Genetics Program, The University of Texas Graduate School of Biomedical Sciences, Houston, Texas 77030, USA. svattathil@utexas.edu
Paul Scheet

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
Population genetics for large-scale sequencing studies of diverse populationsR01HG005855 · NHGRI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Noah Rosenberg, Paul A Scheet · 2010 to 2026
$5.8M
Statistical Methods for Population Genomics and "Next-gen" Sequencing DataR01HG005859 · NHGRI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI SCHEET, PAUL A · 2011 to 2015
$1.9M
NHGRI NIH HHS 1R01HG005859NHGRI NIH HHS R01 HG005855NHGRI NIH HHS R01HG005855NHGRI NIH HHS R01 HG005859
6 · The paper itself

Abstract

Due to limitations of surgical dissection and tumor heterogeneity, tumor samples collected for cancer genomics studies are often heavily diluted with normal tissue or contain subpopulations of cells harboring important aberrations. Methods for profiling tumor-associated allelic imbalance in such scenarios break down at aberrant cell proportions of 10%-15% and below. Here, we present an approach that offers a vast improvement for detection of subtle allelic imbalance, or low proportions of cells harboring aberrant allelic ratio among nonaberrant cells, in unpaired tumor samples using SNP microarrays. We leverage the expected pattern of allele-specific intensity ratios determined by an individual's germline haplotypes, information that has been ignored in existing approaches. We demonstrate our method on real and simulated data from the CRL-2324 breast cancer cell line genotyped on the Illumina 370K array. Assuming a 5 million SNP array, we can detect the presence of aberrant cells in proportions lower than 0.25% in the breast cancer sample, approaching the sensitivity of some minimal residual disease assays. Further, we apply a hidden Markov model to identify copy-neutral LOH (loss of heterozygosity) events as short as 11 Mb in mixtures of only 4% tumor using 370K data. We anticipate our approach will offer a new paradigm for genomic profiling of heterogeneous samples.

Indexed as

Allelic ImbalanceHaplotypesPolymorphism, Single NucleotideBreast NeoplasmsCell Line, TumorDNA, NeoplasmFemaleGenome, HumanGenotyping TechniquesHeterozygoteHumansMarkov ChainsModels, GeneticOligonucleotide Array Sequence AnalysisSensitivity and SpecificityDNA, Neoplasm

Identifiers

PMID23028187
PMCPMC3530675

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.