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Gilean McVean

Researcher at University of Oxford

Publications -  77
Citations -  41543

Gilean McVean is an academic researcher from University of Oxford. The author has contributed to research in topics: Population & Single-nucleotide polymorphism. The author has an hindex of 42, co-authored 77 publications receiving 36519 citations. Previous affiliations of Gilean McVean include University of Cambridge & University of Edinburgh.

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Journal ArticleDOI

The variant call format and VCFtools

TL;DR: VCFtools is a software suite that implements various utilities for processing VCF files, including validation, merging, comparing and also provides a general Perl API.
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The International HapMap Project

John W. Belmont, +145 more
- 18 Dec 2003 - 
TL;DR: The HapMap will allow the discovery of sequence variants that affect common disease, will facilitate development of diagnostic tools, and will enhance the ability to choose targets for therapeutic intervention.
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A haplotype map of the human genome

John W. Belmont, +232 more
TL;DR: A public database of common variation in the human genome: more than one million single nucleotide polymorphisms for which accurate and complete genotypes have been obtained in 269 DNA samples from four populations, including ten 500-kilobase regions in which essentially all information about common DNA variation has been extracted.
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A second generation human haplotype map of over 3.1 million SNPs

Kelly A. Frazer, +237 more
- 18 Oct 2007 - 
TL;DR: The Phase II HapMap is described, which characterizes over 3.1 million human single nucleotide polymorphisms genotyped in 270 individuals from four geographically diverse populations and includes 25–35% of common SNP variation in the populations surveyed, and increased differentiation at non-synonymous, compared to synonymous, SNPs is demonstrated.
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Detecting Novel Associations in Large Data Sets

TL;DR: A measure of dependence for two-variable relationships: the maximal information coefficient (MIC), which captures a wide range of associations both functional and not, and for functional relationships provides a score that roughly equals the coefficient of determination of the data relative to the regression function.