h2 values to use in the instruction: a <-grammar(h2ht,data=df)

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Joined: Fri Sep 30, 2016 6:29 am

h2 values to use in the instruction: a <-grammar(h2ht,data=df)

Postby biancaneve » Fri Sep 30, 2016 12:53 pm

I must calculate heritability of two traits (tr1 and tr2) in order to perform association analysis with Bovine Illumina BeadChip (777,962 markers) using the following function:

Code: Select all

a_tr  <-grammar (h2ht, data=data868)

I have 900 individuals, two fixed effects: farm and year of birth, the traits are the following:
t1 = number of calvings in lifespan of every cow (1 to 12);
t2 = number of days in lifespan of the same cows (from birth to sale for slaughter: 1153 to 5934 days).
the two traits are highly correlated (+ 78%).

1. I used the following function to calculate heritability:

Code: Select all

> h2_tr <- polygenic (tr ~farm+year, kin=gkin, data868, trait.type = "gaussian")

and I obtained reliable heritability values (0.27) for trait 1.
For trait 2, I obtained unreliable values (close to 1), with the following warning: .
“some eigenvalues close/less than 1e-8, setting them to 1e-8 you can also try option llfun='polylik' instead”.
2. Then I tried:

Code: Select all

> h2_tr <- polygenic (tr ~farm+year, kin=gkin, data868, trait.type = "gaussian", llfun=polylik)

and I obtained the same unreliable h2, slightly lower (0.97) but the procedure has been running for 20 hours.
3. Suspecting that the trait was not linear, I added “ opt.method = "nlm", but obtained again h2=09999999.
4. Should I maybe use the “steptol” and “gradtol” ? I tried them with various values and I obtained various h2 estimates, ranging from .17 to .50.
Can you help me?
Last edited by lckarssen on Fri Sep 30, 2016 7:47 pm, edited 1 time in total.
Reason: Formatted R code using [code] tags

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