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Willer CJ, Li Y, Abecasis GR. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics. 2010;26(17):2190-1doi: 10.1093/bioinformatics/btq340.
Willer, C. J., Li, Y., & Abecasis, G. R. (2010). METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics (Oxford, England), 26(17), 2190-1. https://doi.org/10.1093/bioinformatics/btq340
Willer, Cristen J, et al. "METAL: fast and efficient meta-analysis of genomewide association scans." Bioinformatics (Oxford, England) vol. 26,17 (2010): 2190-1. doi: https://doi.org/10.1093/bioinformatics/btq340
Willer CJ, Li Y, Abecasis GR. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics. 2010 Sep 01;26(17):2190-1. doi: 10.1093/bioinformatics/btq340. Epub 2010 Jul 08. PMID: 20616382; PMCID: PMC2922887.
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Bioinformatics. 2010 Sep 01;26(17):2190-1. doi: 10.1093/bioinformatics/btq340. Epub 2010 Jul 08.

METAL: fast and efficient meta-analysis of genomewide association scans.

Bioinformatics (Oxford, England)

Cristen J Willer, Yun Li, Gonçalo R Abecasis

Affiliations

  1. Department of Biostatistics, University of Michigan, 1420 Washington Heights, Ann Arbor, Michigan 48109, USA.

PMID: 20616382 PMCID: PMC2922887 DOI: 10.1093/bioinformatics/btq340

Abstract

SUMMARY: METAL provides a computationally efficient tool for meta-analysis of genome-wide association scans, which is a commonly used approach for improving power complex traits gene mapping studies. METAL provides a rich scripting interface and implements efficient memory management to allow analyses of very large data sets and to support a variety of input file formats.

AVAILABILITY AND IMPLEMENTATION: METAL, including source code, documentation, examples, and executables, is available at http://www.sph.umich.edu/csg/abecasis/metal/.

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