Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2014 Oct;30(19):2828-9.
doi: 10.1093/bioinformatics/btu367. Epub 2014 Jun 3.

RAREMETAL: fast and powerful meta-analysis for rare variants

Shuang Feng  1 , Dajiang Liu  1 , Xiaowei Zhan  1 , Mary Kate Wing  1 , Gonçalo R Abecasis  1
Affiliations

RAREMETAL: fast and powerful meta-analysis for rare variants

Shuang Feng et al. Bioinformatics. 2014 Oct.

Abstract

Summary: RAREMETAL is a computationally efficient tool for meta-analysis of rare variants genotyped using sequencing or arrays. RAREMETAL facilitates analyses of individual studies, accommodates a variety of input file formats, handles related and unrelated individuals, executes both single variant and burden tests and performs conditional association analyses.

Availability and implementation: http://genome.sph.umich.edu/wiki/RAREMETAL for executables, source code, documentation and tutorial.

PubMed Disclaimer

Figures

Fig. 1.
Fig. 1.
Automatically generated QQ and Manhattan plots by RAREMETAL and RMW. (a) Manhattan plot from single variant analysis. (b) Manhattan plot from gene-level burden tests
See this image and copyright information in PMC

References

    1. Abecasis GR, et al. Merlin—rapid analysis of dense genetic maps using sparse gene flow trees. Nat. Genet. 2002;30:97–101. - PubMed
    1. Danecek P, et al. The variant call format and VCFtools. Bioinformatics. 2011;27:2156–2158. - PMC - PubMed
    1. Kang HM, et al. Variance component model to account for sample structure in genome-wide association studies. Nat. Genet. 2010;42:348–354. - PMC - PubMed
    1. Lee S, et al. General framework for meta-analysis of rare variants in sequencing association studies. Am. J. Hum. Genet. 2013;93:42–53. - PMC - PubMed
    1. Li B, Leal SM. Methods for detecting associations with rare variants for common diseases: application to analysis of sequence data. Am. J. Hum. Genet. 2008;83:311–321. - PMC - PubMed

Publication types