covariance between relatives
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Genetics ◽  
2010 ◽  
Vol 184 (4) ◽  
pp. 1037-1050 ◽  
Author(s):  
Omri Tal ◽  
Eva Kisdi ◽  
Eva Jablonka

2007 ◽  
Vol 50 (3) ◽  
pp. 294-308 ◽  
Author(s):  
C. Baes ◽  
N. Reinsch

Abstract. The inverse of the conditional gametic relationship matrix (G-1) for a marked quantitative trait locus (MQTL) is required for estimation of gametic effects in best linear unbiased prediction (BLUP) of breeding values if marker data are available. Calculation of the "condensed" gametic relationship matrix G* – a version of G where linear dependencies have been removed – and its inverse G*-1 is described using a series of simplified equations following a known algorithm. The software program COBRA (covariance between relatives for a marked QTL) is introduced, and techniques for storing and computing the condensed gametic relationship matrix G* and the non-zero elements of its inverse are discussed. The program operates with both simple pedigrees and those augmented by transmission probabilities derived from marker data. Using sparse matrix storage techniques, G* and its inverse can be efficiently stored in computer memory. COBRA is written in FORTRAN 90/95 and runs on a variety of computers. Pedigree data and information for a single MQTL in the German Holstein population are used to test the efficiency of the program.


2002 ◽  
Vol 34 (6) ◽  
pp. 657 ◽  
Author(s):  
Yuefu Liu ◽  
Gerald B Jansen ◽  
Ching Y Lin

1995 ◽  
Vol 27 (3) ◽  
pp. 251 ◽  
Author(s):  
T Wang ◽  
RL Fernando ◽  
S Beek ◽  
M Grossman ◽  
JAM van Arendonk

1993 ◽  
Vol 87 (4) ◽  
pp. 423-430 ◽  
Author(s):  
L. L. Lo ◽  
R. L. Fernando ◽  
M. Grossman

1985 ◽  
Vol 45 (3) ◽  
pp. 287-297 ◽  
Author(s):  
Bruce Riska ◽  
J. J. Rutledge ◽  
William R. Atchley

SummaryCovariance between direct and maternal genetic effects on body weight in random-bred ICR mice at 2 through 10 weeks of age was estimated from cross-fostering experiments. The covariance contributes only a few percent of phenotypic variance at 2 weeks, but increases to 10–15% at later ages. Nearly all estimates are positive. We suggest that genes active during later parts of growth affect maternal performance more than those active during early growth, causing increased covariance at later ages. A model of combined genetic and persistent environmental effects on maternal performance is presented. Persistent effects of genetic or environmental variation in recent ancestors can influence covariance between relatives and response to selection.


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