Genome-wide complex trait analysis (GCTA): methods, data analyses, and interpretations
Date
2013
Authors
Yang, J.
Lee, S.H.
Goddard, M.E.
Visscher, P.M.
Editors
Gondro, C.
Werf, J.
Hayes, B.
Werf, J.
Hayes, B.
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Book chapter
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Source details - Title: Genome-wide association studies and genomic prediction, 2013 / Gondro, C., Werf, J., Hayes, B. (ed./s), Ch.9, pp.215-236
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Abstract
Estimating genetic variance is traditionally performed using pedigree analysis. Using high-throughput DNA marker data measured across the entire genome it is now possible to estimate and partition genetic variation from population samples.
In this chapter, we introduce methods and a software tool called Genome-wide Complex Trait Analysis (GCTA) to estimate genomic relationships between pairs of conventionally unrelated individuals using genome-wide single nucleotide polymorphism (SNP) data, to estimate variance explained by all SNPs simultaneously on genomic or chromosomal segments or over the whole genome, and to perform a joint and conditional multiple SNPs association analysis using summary statistics from a meta-analysis of genome-wide association studies and linkage disequilibrium between SNPs estimated from a reference sample.
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Copyright 2013 Springer Science & Business Media