Evidence map›Paper›PMID 28196472›Full record

ArticleBMC genomics2017

PreMeta: a tool to facilitate meta-analysis of rare-variant associations.

Zheng-Zheng Tang, Paul Bunn, Ran Tao, Zhouwen Liu, Dan-Yu Lin

Abstract read
In one paragraph

Article in BMC genomics, 2017. 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

5 authors.

Zheng-Zheng TangDepartment of Biostatistics, Vanderbilt University School of Medicine, Nashville, 37203, TN, USA. z.tang@vanderbilt.edu.
Paul BunnDepartment of Biostatistics, University of North Carolina, Chapel Hill, 37203, NC, USA.
Ran TaoDepartment of Biostatistics, University of North Carolina, Chapel Hill, 37203, NC, USA.
Zhouwen LiuDepartment of Biostatistics, Vanderbilt University School of Medicine, Nashville, 37203, TN, USA.
Dan-Yu LinDepartment of Biostatistics, University of North Carolina, Chapel Hill, 37203, NC, USA.

Funding

Statistical Methods for Cancer Clinical TrialsP01CA142538 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI KOSOROK, MICHAEL R · 2010 to 2019
$21.3M
Building Interdisciplinary Research Careers in Women's HealthK12HD043483 · NICHD · VANDERBILT UNIVERSITY MEDICAL CENTER · PI HARTMANN, KATHERINE E, MAJOR, AMY S · 2002 to 2023
$10.3M
STATISTICAL METHODS IN CURRENT CANCER RESEARCHR01CA082659 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI LIN, DANYU · 2000 to 2016
$3.7M
Semiparametric Regression Analysis of Censored DataR01GM047845 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI LIN, DANYU · 1997 to 2018
$2.9M
NCI NIH HHS P01 CA142538NCI NIH HHS R01 CA082659NICHD NIH HHS K12 HD043483NIGMS NIH HHS R01 GM047845
6 · The paper itself

Abstract

backgroundMeta-analysis is essential to the discovery of rare variants that influence complex diseases and traits. Four major software packages, namely MASS, MetaSKAT, RAREMETAL, and seqMeta, have been developed to perform meta-analysis of rare-variant associations. These packages first generate summary statistics for each study and then perform the meta-analysis by combining the summary statistics. Because of incompatible file formats and non-equivalent summary statistics, the output files from the study-level analysis of one package cannot be directly used to perform meta-analysis in another package.

resultsWe developed a computationally efficient software program, PreMeta, to resolve the non-compatibility of the four software packages and to facilitate meta-analysis of large-scale sequencing studies in a consortium setting. PreMeta reformats the output files of study-level summary statistics generated by the four packages (text files produced by MASS and RAREMETAL, binary files produced by MetaSKAT, and R data files produced by seqMeta) and translates the summary statistics from one form to another, such that the summary statistics from any package can be used to perform meta-analysis in any other package. With this tool, consortium members are not required to use the same software for study-level analyses. In addition, PreMeta checks for allele mismatches, corrects summary statistics, and allows the rescaled inverse normal transformation to be performed at the meta-analysis stage by rescaling summary statistics.

conclusionsPreMeta processes summary statistics from the four packages to make them compatible and avoids the need to redo study-level analyses. PreMeta documentation and executable are available at: http://dlin.web.unc.edu/software/premeta .

Indexed as

Genetic Association StudiesGenetic VariationSoftwareComputational BiologyFemaleHumansMaleMeta-Analysis as TopicWeb BrowserGene-based association testsMASSMetaSKATRAREMETALseqMetaSummary statistics

Identifiers

PMID28196472
PMCPMC5310051

What OpenQuestion holds

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Registered trials

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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.