Evidence map›Paper›PMID 29556250›Full record

ArticleFrontiers in genetics2018

Determining Genetic Causal Variants Through Multivariate Regression Using Mixture Model Penalty.

V S Sundar, Chun-Chieh Fan, Dominic Holland, Anders M Dale

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

V S SundarCenter for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, United States.
Chun-Chieh FanCenter for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, United States.
Dominic HollandCenter for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, United States.
Anders M DaleCenter for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, United States.

Funding

ABCD-USA Consortium: Data Analysis, Informatics and Resource CenterU24DA041123 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ANDERS M DALE · 2015 to 2026
$51.5M
NIDA NIH HHS U24 DA041123
6 · The paper itself

Abstract

With the availability of high-throughput sequencing data, identification of genetic causal variants accurately requires the efficient incorporation of function annotation data into the optimization routine. This motivates the need for development of novel methods for genome wide association studies with special focus on fine-mapping capabilities. A penalty function method that is simple to implement and capable of integrating functional annotation information into the estimation procedure, is proposed in this work. The idea is to use the prior distribution of the effect sizes explicitly as a penalty function. The estimates obtained are shown to be better correlated with the true effect sizes (in comparison with a few existing techniques). An increase in the positive and negative predictive value is demonstrated using Hapgen2 simulated data.

Indexed as

effect sizesfine-mappingmixture modeloptimizationSNP discovery

Identifiers

PMID29556250
PMCPMC5844985

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.