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Table 5 Number of random covariates (windows) and computation time for each model

From: Fixed-length haplotypes can improve genomic prediction accuracy in an admixed dairy cattle population

Modela

Number of random effectsb

Computation time (h)d

Fatc

Lwtc

SCSc

Fatc

Lwtc

SCSc

BayesA

SNP

37,226

37,356

37,229

13.1

6.6

13.0

Hap125e

37,848

37,775

37,898

15.2

7.8

15.1

Hap250f

64,724

64,634

64,730

23.5

13.1

24.4

BayesB

SNP

18,589

18,637

18,629

10.0

5.1

9.9

Hap125e

18,899

18,831

18,954

13.6

6.2

13.9

Hap250f

32,332

32,273

32,388

18.1

9.2

18.0

BayesN

SNP

17,748 (4701)

17,639 (4671)

18,254 (4805)

26.7

12.5

25.6

Hap125e

18,451 (8264)

18,303 (8223)

18,711 (8344)

30.2

16.0

30.0

Hap250f

31,596 (4737)

31,281 (4706)

32,103 (4809)

37.6

18.9

38.1

  1. aSNP = SNP model with 250 kb windows
  2. bAverage number of SNPs or haplotype alleles fitted in each chain of the MCMC
  3. cFat = Milk fat yield; Lwt = liveweight; SCS = somatic cell score
  4. dComputation time for running the analysis on the training set containing all breeds with a chain length of 41,000
  5. eHap125 = Haplotypes of length 125 kb, fitting only haplotype alleles >10% frequency in training data set
  6. fHap250 = Haplotypes of length 250 kb, fitting only haplotype alleles >1% frequency in training data set
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Genetics Selection Evolution

ISSN: 1297-9686