Synbreed: A framework for the analysis of genomic prediction data using R

Bioinformatics

Volumn 28, Issue 15, 2012, Pages 2086-2087

  Wimmer, Valentin ^a   Albrecht, Theresa ^a   Auinger, Hans Jürgen ^a   Schön, Chris Carolin ^a  

^a TECHNICAL UNIVERSITY OF MUNICH   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; BIOLOGY; COMPUTER PROGRAM; COMPUTER SIMULATION; GENOMICS; GENOTYPING TECHNIQUE; INFORMATION PROCESSING; METHODOLOGY; STATISTICAL MODEL;

ALGORITHMS; AUTOMATIC DATA PROCESSING; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; GENOMICS; GENOTYPING TECHNIQUES; LINEAR MODELS; SOFTWARE;

EID: 84865139666     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/bts335     Document Type: Article

References (10)

1. Albrecht,T. et al. (2011) Genome-based prediction of testcross values in maize. Theor. Appl. Genet., 123, 339-350.
2. Broman,K.W. et al. (2003) R/qtl: Qtl mapping in experimental crosses. Bioinformatics, 7, 889-890.
3. Browning,B.L. and Browning,S.R. (2009) A unified approach to genotype imputation and haplotype-phase inference for large data sets of trios and unrelated individuals. Am. J. Hum. Genet., 84, 210-223.
4. Clifford,D. and McCullagh,P. (2012) The regress package. R package version 1.3-8.
5. Gilmour,A.R. et al. (2009) ASREML User Guide Release 3.0. VSN International Ltd, Hemel Hempstead, UK.
6. Habier,D. et al. (2007) The impact of genetic relationship information on genomeassisted breeding values. Genetics, 177, 2389-2397.
7. Meuwissen,T.H.E. et al. (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics, 157, 1819-1829.
8. Pérez,P. et al. (2010) Genomic-enabled prediction based on molecular markers and pedigree using the BLR package in R. Plant Genome, 3, 106-116.
9. Purcell,S. et al. (2007) PLINK: a toolset for whole-genome association and populationbased linkage analysis. Am. J. Hum. Genet., 81, 559-575.
10. R Development Core Team. (2012) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.