Re: Random SNP effects

Dear Denis,

Concerning:
I was intending to run a random SNP model to estimate the variance of
total phenotypic variance accounted for by the SNP. For simplicity, I
would like to assume an IID structure for the SNP.
I was wondering if the following model definition captures this.

Trait ~ mu fixed_effects !r id snp1 !f contemp
0 0 1
id 2
1 0 US 0.4 !GP
id

Also would there be a way to make ASReml output the Sum of Squares in
the .asr file?

You can write the model in that way, but the last 4 lines are unnecessary
as the model specified is the default model.
i.e.

Trait ~ mu fixed_effects !r id 0.4 !GP snp1 !f contemp
0

specifies the same model.

Now if you have a relatively large number of SNPs you want to fit in this
way, there are some tricks available in ASReml3
to make this easier (i.e. faster). In particular, there is a large
overhead reading the data if you have to read 1000 SNP
variables from the data file, and then only use a few in the model, and
you do this 1000 times. So if you put the SNP data
in separate files and use !MBF to just access the particular SNPs you
want, this speeds the processing.

Further, the !CYCLE command has been extended so it is easier to cycle
through the say 1000 models taking one SNP each cycle.
And a summary line is written to the .asr file which can be extracted by
the unix utility 'grep' and sorted to identify the best fits.

Now, concerning the Sum of Squares: it cannot be directly extracted but
you can calculate an equivalent statistic from the
Residual variance which is reported along with the REML LogL.

The asreml3alpha download registration page is:
http://www.austatgen.org/asreml3alpha.php
There are asreml3alpha forums at: http://www.austatgen.org/asreml3forum

May Jesus Christ be gracious to you in 2008,

Arthur Gilmour, His servant .
 
Mixed model regression mapping for QTL detection in experimental crosses.
Computational Statistics and Data Analysis 51:3749-3764 at
http://dx.doi.org/10.1016/j.csda.2006.12.031

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Received on Thu Apr 08 2008 - 09:52:42 EST