Evidence map›Paper›PMID 22718036›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2012

Clinical utility of sequence-based genotype compared with that derivable from genotyping arrays.

Alexander A Morgan, Rong Chen, Atul Janardhan Butte

Abstract readComparative Study
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. The coming age of data-driven medicine: translational bioinformatics' next frontier.Journal of the American Medical Informatics Association : JAMIA · 2012
    Article
  2. Translational bioinformatics embraces big data.Yearbook of medical informatics · 2012
    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

3 authors.

Alexander A MorganDepartment of Biochemistry, Stanford Genome Technology Center, Stanford University, Stanford, California, USA. alexmo@stanford.edu
Rong Chen
Atul Janardhan Butte

Funding

POSTDOCTORAL TRAINING IN MEDICAL INFORMATION SCIENCEST15LM007033 · NLM · STANFORD UNIVERSITY · PI SYLVIA KATINA PLEVRITIS · 1985 to 2026
$25.5M
Integrating Microarray and Proteomic Data by Ontology-based AnnotationR01LM009719 · NLM · STANFORD UNIVERSITY · PI BUTTE, ATUL J · 2008 to 2011
$1.1M
NLM NIH HHS R01 LM009719NLM NIH HHS T15 LM007033
6 · The paper itself

Abstract

objectiveWe investigated the common-disease relevant information obtained from sequencing compared with that reported from genotyping arrays. MATERIALS AND

methodsUsing 187 publicly available individual human genomes, we constructed genomic disease risk summaries based on 55 common diseases with reported gene-disease associations in the research literature using two different risk models, one based on the product of likelihood ratios and the other on the allelic variant with the maximum associated disease risk. We also constructed risk profiles based on the single nucleotide polymorphisms (SNPs) of these individuals that could be measured or imputed from two common genotyping array platforms.

resultsWe show that the model risk predictions derived from sequencing differ substantially from those obtained from the SNPs measured on commercially available genotyping arrays for several different non-monogenic diseases, although high density genotyping arrays give identical results for many diseases.

conclusionsOur approach may be used to compare the ability of different platforms to probe known genetic risks disease by disease.

Indexed as

Oligonucleotide Array Sequence AnalysisSequence Analysis, DNAGenetic Predisposition to DiseaseGenetic TestingGenotypeHumansLikelihood Functions

Identifiers

PMID22718036
PMCPMC3392859

What OpenQuestion holds

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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.