Post by Jian Yang on Nov 24, 2015 7:12:27 GMT
Zaitlen et al. (2013 PLoS Genetics) proposed a method to estimate pedigree-based and SNP-based h2 simultaneously in one model using family data. The main advantage of this method is that it allows us to estimate SNP-based h2 in family data without having to remove related individuals. The method has now been implemented in GCTA.
--make-bK 0.05
The default value is 0.05. This option will set the GRM off-diagonal elements that are below the threshold to 0.
Examples
# Making a GRM from all SNPs in a family data set
gcta64 --bfile test --make-grm --out test
# Creating an additional GRM from the GRM above (setting the off-diagonals that are < 0.05 to 0)
gcta64 --grm test --make-bK 0.05 --out test_bK
An example of the mgrm.txt file
# Running a REML analysis with two GRMs
gcta64 --reml --mgrm mgrm.txt --pheno test.phen --out test_bKsK
Here is an example of the output file (test_bKsK.hsq)
where "V(G1) / Vp" provides an estimate of SNP-based h2 (h2SNP), "Sum of V(G) / Vp" provides an estimate of pedigree-based h2 (h2ped), and V(G2) / Vp = h2ped - h2SNP.
References
Method for estimating the GRM: Yang et al. (2010) Common SNPs explain a large proportion of the heritability for human height. Nat Genet. 42(7): 565-9. [PubMed ID: 20562875]
The Zaitlen et al. method: Zaitlen N, Kraft P, Patterson N, Pasaniuc B, Bhatia G, Pollack S, Price AL (2013) Using extended genealogy to estimate components of heritability for 23 quantitative and dichotomous traits. PLoS Genet. 2013 May;9(5):e1003520. PubMed ID: 23737753]
REML analysis and GCTA Software: Yang J, Lee SH, Goddard ME and Visscher PM. GCTA: a tool for Genome-wide Complex Trait Analysis. Am J Hum Genet. 2011 Jan 88(1): 76-82. [PubMed ID: 21167468]
--make-bK 0.05
The default value is 0.05. This option will set the GRM off-diagonal elements that are below the threshold to 0.
Examples
# Making a GRM from all SNPs in a family data set
gcta64 --bfile test --make-grm --out test
# Creating an additional GRM from the GRM above (setting the off-diagonals that are < 0.05 to 0)
gcta64 --grm test --make-bK 0.05 --out test_bK
An example of the mgrm.txt file
test
test_bK
# Running a REML analysis with two GRMs
gcta64 --reml --mgrm mgrm.txt --pheno test.phen --out test_bKsK
Here is an example of the output file (test_bKsK.hsq)
Source Variance SE
V(G1) 0.294615 0.102976
V(G2) 0.322424 0.144884
V(e) 0.377467 0.104458
Vp 0.994506 0.027059
V(G1)/Vp 0.296242 0.102655
V(G2)/Vp 0.324205 0.145112
Sum of V(G)/Vp 0.620447 0.105741
logL -1357.892
n 2753where "V(G1) / Vp" provides an estimate of SNP-based h2 (h2SNP), "Sum of V(G) / Vp" provides an estimate of pedigree-based h2 (h2ped), and V(G2) / Vp = h2ped - h2SNP.
References
Method for estimating the GRM: Yang et al. (2010) Common SNPs explain a large proportion of the heritability for human height. Nat Genet. 42(7): 565-9. [PubMed ID: 20562875]
The Zaitlen et al. method: Zaitlen N, Kraft P, Patterson N, Pasaniuc B, Bhatia G, Pollack S, Price AL (2013) Using extended genealogy to estimate components of heritability for 23 quantitative and dichotomous traits. PLoS Genet. 2013 May;9(5):e1003520. PubMed ID: 23737753]
REML analysis and GCTA Software: Yang J, Lee SH, Goddard ME and Visscher PM. GCTA: a tool for Genome-wide Complex Trait Analysis. Am J Hum Genet. 2011 Jan 88(1): 76-82. [PubMed ID: 21167468]