02796naa a2200265 a 450000100080000000500110000800800410001902200140006002400490007410000160012324501020013926000090024150000810025052019030033165000210223465000250225565300320228065300220231265300550233465300140238965300210240370000160242470000160244077300740245610501062019-06-18       2014    bl uuuu     u00u1 u    #d  a0022-03027 ahttp://dx.doi.org/10.3168/jds.2013-77522DOI1 aMISZTAL, I.  aUsing recursion to compute the inverse of the genomic relationship matrix.h[electronic resource]  c2014  aArticle history: Received November 22, 2013. //  Accepted February 10, 2014.  aABSTRACT.  Computing the inverse of the genomic relationship matrix using recursion was investigated. A traditional algorithm to invert the numerator relationship matrix is based on the observation that the conditional expectation for an additive effect of 1 animal given the effects of all other animals depends on the effects of its sire and dam only, each with a coefficient of 0.5. With genomic relationships, such an expectation depends on all other genotyped animals, and the coefficients do not have any set value. For each animal, the coefficients plus the conditional variance can be called a genomic recursion. If such recursions are known, the mixed model equations can be solved without explicitly creating the inverse of the genomic relationship matrix. Several algorithms were developed to create genomic recursions. In an algorithm with sequential updates, genomic recursions are created animal by animal. That algorithm can also be used to update a known inverse of a genomic relationship matrix for additional genotypes. In an algorithm with forward updates, a newly computed recursion is immediately applied to update recursions for remaining animals. The computing costs for both algorithms depend on the sparsity pattern of the genomic recursions, but are lower or equal than for regular inversion. An algorithm for proven and young animals assumes that the genomic recursions for young animals contain coefficients only for proven animals. Such an algorithm generates exact genomic EBV in genomic BLUP and is an approximation in single-step genomic BLUP. That algorithm has a cubic cost for the number of proven animals and a linear cost for the number of young animals. The genomic recursions can provide new insight into genomic evaluation and possibly reduce costs of genetic predictions with extremely large numbers of genotypes. © 2014 American Dairy Science Association.  aGENÓMICA ANIMAL  aSELECCIÓN GENÓMICA  aGENOMIC RELATIONSHIP MATRIX  aGENOMIC SELECTION  aPRECONDITIONED CONJUGATE GRADIENTE (PCG) ALGORITHM  aRECURSION  aSINGLE-STEP BLUP1 aLEGARRA, A.1 aAGUILAR, I.  tJournal of Dairy Science, 2014gv.97, no.6, p.3943-3952. OPEN ACCESS.