Compression distance can discriminate animals by genetic profile, build relationship matrices and estimate breeding values
作者： Nicholas J. Hudson , Laercio Porto-Neto , James W. Kijas , Antonio Reverter
DOI: 10.1186/S12711-015-0158-9
关键词:
摘要: Background Genetic relatedness is currently estimated by a combination of traditional pedigree-based approaches (i.e. numerator relationship matrices, NRM) and, given the recent availability molecular information, using marker genotypes (via genomic GRM). To date, GRM are computed genome-wide pair-wise SNP (single nucleotide polymorphism) correlations.
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Joseph Lachance, Sarah A. Tishkoff, SNP ascertainment bias in population genetic analyses: Why it is important, and how to correct it BioEssays. ,vol. 35, pp. 780- 786 ,(2013) , 10.1002/BIES.201300014
Jakris Eu-Ahsunthornwattana, E Nancy Miller, Michaela Fakiola, Wellcome Trust Case Control Consortium 2, Selma MB Jeronimo, Jenefer M Blackwell, Heather J Cordell, None, Comparison of Methods to Account for Relatedness in Genome-Wide Association Studies with Family-Based Data PLoS Genetics. ,vol. 10, pp. e1004445- ,(2014) , 10.1371/JOURNAL.PGEN.1004445
C.R. Henderson, Rapid Method for Computing the Inverse of a Relationship Matrix Journal of Dairy Science. ,vol. 58, pp. 1727- 1730 ,(1975) , 10.3168/JDS.S0022-0302(75)84776-X
Sewall Wright, Coefficients of Inbreeding and Relationship The American Naturalist. ,vol. 56, pp. 330- 338 ,(1922) , 10.1086/279872
Nicholas J Hudson, Laercio R Porto-Neto, James Kijas, Sean McWilliam, Ryan J Taft, Antonio Reverter, Information compression exploits patterns of genome composition to discriminate populations and highlight regions of evolutionary interest BMC Bioinformatics. ,vol. 15, pp. 66- 66 ,(2014) , 10.1186/1471-2105-15-66
Sharon R. Browning, Brian L. Browning, High-Resolution Detection of Identity by Descent in Unrelated Individuals American Journal of Human Genetics. ,vol. 86, pp. 526- 539 ,(2010) , 10.1016/J.AJHG.2010.02.021
M. R. S. Fortes, A. Reverter, M. Kelly, R. McCulloch, S. A. Lehnert, Genome‐wide association study for inhibin, luteinizing hormone, insulin‐like growth factor 1, testicular size and semen traits in bovine species Journal of Andrology. ,vol. 1, pp. 644- 650 ,(2013) , 10.1111/J.2047-2927.2013.00101.X
Qiankun Zhang, Hong-Gu Lee, Jung-A Han, Eun Bae Kim, Sang Kee Kang, Jinlong Yin, Myunggi Baik, Yannan Shen, Sang-Hoon Kim, Kang-Seok Seo, Yun-Jaie Choi, None, Differentially expressed proteins during fat accumulation in bovine skeletal muscle. Meat Science. ,vol. 86, pp. 814- 820 ,(2010) , 10.1016/J.MEATSCI.2010.07.002
B.J. Hayes, P.J. Bowman, A.J. Chamberlain, M.E. Goddard, Invited review: Genomic selection in dairy cattle: progress and challenges. Journal of Dairy Science. ,vol. 92, pp. 433- 443 ,(2009) , 10.3168/JDS.2008-1646
Daniel Gianola, Xiao-Lin Wu, Eduardo Manfredi, Henner Simianer, A non-parametric mixture model for genome-enabled prediction of genetic value for a quantitative trait Genetica. ,vol. 138, pp. 959- 977 ,(2010) , 10.1007/S10709-010-9478-4