Evidence map›Paper›PMID 24711653›Full record

ArticleBioinformatics (Oxford, England)2014

Covariate-modulated local false discovery rate for genome-wide association studies.

Rong W Zablocki, Andrew J Schork, Richard A Levine, Ole A Andreassen, Anders M Dale, Wesley K Thompson

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Bioinformatics (Oxford, England), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Analysis of the Associations Between the Human Fecal Microbiome and Bone Density, Structure, and Strength: The Osteoporotic Fractures in Men (MrOS) Cohort.Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research · 2022
    Article
  7. Article
  8. Article
  9. Article
  10. Bayesian GWAS with Structured and Non-Local Priors.Bioinformatics (Oxford, England) · 2020
    Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Weighted False Discovery Rate Control in Large-Scale Multiple Testing.Journal of the American Statistical Association · 2018
    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

6 authors.

Rong W ZablockiComputational Science Research Center, San Diego State University, San Diego, CA 92182, USA, Cognitive Sciences Graduate Program, University of California at San Diego, La Jolla, CA 92093, USA, Department of Mathematics and Statistics, San Diego State University, San Diego, CA 92182, USA, Institute of Clinical Medicine, University of Oslo, Oslo, 0424, Norway, Multimodal Imaging Laboratory and Department of Psychiatry, University of California at San Diego, La Jolla, CA 92093, USA.
Andrew J SchorkComputational Science Research Center, San Diego State University, San Diego, CA 92182, USA, Cognitive Sciences Graduate Program, University of California at San Diego, La Jolla, CA 92093, USA, Department of Mathematics and Statistics, San Diego State University, San Diego, CA 92182, USA, Institute of Clinical Medicine, University of Oslo, Oslo, 0424, Norway, Multimodal Imaging Laboratory and Department of Psychiatry, University of California at San Diego, La Jolla, CA 92093, USA.
Richard A LevineComputational Science Research Center, San Diego State University, San Diego, CA 92182, USA, Cognitive Sciences Graduate Program, University of California at San Diego, La Jolla, CA 92093, USA, Department of Mathematics and Statistics, San Diego State University, San Diego, CA 92182, USA, Institute of Clinical Medicine, University of Oslo, Oslo, 0424, Norway, Multimodal Imaging Laboratory and Department of Psychiatry, University of California at San Diego, La Jolla, CA 92093, USA.
Ole A AndreassenComputational Science Research Center, San Diego State University, San Diego, CA 92182, USA, Cognitive Sciences Graduate Program, University of California at San Diego, La Jolla, CA 92093, USA, Department of Mathematics and Statistics, San Diego State University, San Diego, CA 92182, USA, Institute of Clinical Medicine, University of Oslo, Oslo, 0424, Norway, Multimodal Imaging Laboratory and Department of Psychiatry, University of California at San Diego, La Jolla, CA 92093, USA.
Anders M DaleComputational Science Research Center, San Diego State University, San Diego, CA 92182, USA, Cognitive Sciences Graduate Program, University of California at San Diego, La Jolla, CA 92093, USA, Department of Mathematics and Statistics, San Diego State University, San Diego, CA 92182, USA, Institute of Clinical Medicine, University of Oslo, Oslo, 0424, Norway, Multimodal Imaging Laboratory and Department of Psychiatry, University of California at San Diego, La Jolla, CA 92093, USAComputational Science Research Center, San Diego State University, San Diego, CA 92182, USA, Cognitive Sciences Graduate Program, University of California at San Diego, La Jolla, CA 92093, USA, Department of Mathematics and Statistics, San Diego State University, San Diego, CA 92182, USA, Institute of Clinical Medicine, University of Oslo, Oslo, 0424, Norway, Multimodal Imaging Laboratory and Department of Psychiatry, University of California at San Diego, La Jolla, CA 92093, USAComputational Science Research Center, San Diego State University, San Diego, CA 92182, USA, Cognitive Sciences Graduate Program, University of California at San Diego, La Jolla, CA 92093, USA, Department of Mathematics and Statistics, San Diego State University, San Diego, CA 92182, USA, Institute of Clinical Medicine, University of Oslo, Oslo, 0424, Norway, Multimodal Imaging Laboratory and Department of Psychiatry, University of California at San Diego, La Jolla, CA 92093, USA.
Wesley K ThompsonComputational Science Research Center, San Diego State University, San Diego, CA 92182, USA, Cognitive Sciences Graduate Program, University of California at San Diego, La Jolla, CA 92093, USA, Department of Mathematics and Statistics, San Diego State University, San Diego, CA 92182, USA, Institute of Clinical Medicine, University of Oslo, Oslo, 0424, Norway, Multimodal Imaging Laboratory and Department of Psychiatry, University of California at San Diego, La Jolla, CA 92093, USA.

Funding

Mapping Individual Cognitive Differences to Neural Variance and School ReadinessR01HD061414 · NICHD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI JERNIGAN, TERRY L. · 2010 to 2014
$3.3M
Identifying the Polygenic Basis of the Human Brain and Psychiatric DisordersR01MH100351 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI CHEN, CHI-HUA · 2013 to 2017
$2.1M
Polygenicity, Pleiotrophy and Power: Novel Statistical Methods for Gene DiscoveryR01GM104400 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI THOMPSON, WESLEY KURT · 2014 to 2017
$1.6M
Multivariate CART for survival with dental applicationsR01DE019656 · NIDCR · CREIGHTON UNIVERSITY · PI NUNN, MARTHA E · 2011 to 2013
$695k
NICHD NIH HHS R01 HD061414NIDCR NIH HHS R01 DE019656NIGMS NIH HHS R01 GM104400NIMH NIH HHS R01 MH100351
6 · The paper itself

Abstract

motivationGenome-wide association studies (GWAS) have largely failed to identify most of the genetic basis of highly heritable diseases and complex traits. Recent work has suggested this could be because many genetic variants, each with individually small effects, compose their genetic architecture, limiting the power of GWAS, given currently obtainable sample sizes. In this scenario, Bonferroni-derived thresholds are severely underpowered to detect the vast majority of associations. Local false discovery rate (fdr) methods provide more power to detect non-null associations, but implicit assumptions about the exchangeability of single nucleotide polymorphisms (SNPs) limit their ability to discover non-null loci.

methodsWe propose a novel covariate-modulated local false discovery rate (cmfdr) that incorporates prior information about gene element-based functional annotations of SNPs, so that SNPs from categories enriched for non-null associations have a lower fdr for a given value of a test statistic than SNPs in unenriched categories. This readjustment of fdr based on functional annotations is achieved empirically by fitting a covariate-modulated parametric two-group mixture model. The proposed cmfdr methodology is applied to a large Crohn's disease GWAS.

resultsUse of cmfdr dramatically improves power, e.g. increasing the number of loci declared significant at the 0.05 fdr level by a factor of 5.4. We also demonstrate that SNPs were declared significant using cmfdr compared with usual fdr replicate in much higher numbers, while maintaining similar replication rates for a given fdr cutoff in de novo samples, using the eight Crohn's disease substudies as independent training and test datasets. Availability an implementation: https://sites.google.com/site/covmodfdr/ CONTACT: : wes.stat@gmail.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

Analysis of VarianceBayes TheoremComputational BiologyFalse Positive ReactionsGenome-Wide Association StudyHumansPolymorphism, Single Nucleotide

Identifiers

PMID24711653
PMCPMC4103587

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.