[GenABEL-dev] Interesting idea by Gulnara Svischeva

[Yury Aulchenko]

Hi William,

This sounds very interesting indeed!

It would be great to have such linear method implemented in GenA :)

best wishes,
Yurii
-------------------------------------------------------
Yurii Aulchenko, PhD, Dr. Habil.
Independent researcher and consultant
yurii [dot] aulchenko [at] gmail [dot] com

On Oct 11, 2011, at 9:55 PM, Astle, William J wrote:

> Hi all,
> 
> This might be of interest, 
> 
> best wishes 
> 
> Will
> 
> >
> >
> > Dear William,
> >
> > My name is Christoph Lippert. I am a PhD student from the Max Planck Institute for Developmental Biology in Tuebingen, currently working on Mixed Models for GWAS.
> >
> > Recently, we had a paper in Nature Methods, where among other results we presented a way to optimize the ratio of variance parameters for genome-wide SNPs in a mixed model with only a single cubic operation.
> >Last week, I heard that you had a similar result in your thesis. I would be highly interested in your derivation of that result.
> > Could you perhaps send me a copy of your thesis or a writeup of that result? This would be highly appreciated.
> >
> > Thank you,
> > Christoph
> >
> > P.S.: If you are interested in our paper, here is the link:
> > http://www.nature.com/nmeth/journal/vaop/ncurrent/abs/nmeth.1681.html
> 
> 
> On 8 Oct 2011, at 04:37, L.C. Karssen wrote:
> 
>> Dear list,
>> 
>> I was going through the changelog of GenABEL and saw that Gulya's
>> poly_eigen is the default method for polygenic() since version 1.6-8. I
>> did a quick comparison on the computation speed of the three methods
>> (polygenic_hglm, polygenic with polylik and with poly_eigen) on our
>> population and even though I knew what to expect from Yurii's results, I
>> am still impressed at the speedup! 
>> 
>> I was wondering, is there a publication on this method/implementation?
>> Has there been any comparison of poly_eigen vs. the old method (in terms
>> of variance, lambda etc.? In February/March this year there was a
>> discussion on this list where Yurii compared the polylik method with
>> polygenic_hglm, but I haven't seen anything similar on the poly_eigen
>> method.
>> 
>> 
>> Enjoy the weekend,
>> 
>> Lennart.
>> 
>> 
>> On vr, 2011-05-20 at 21:16 +0200, Yurii Aulchenko wrote:
>>> In attached PDF I show the timing for running 'polygenic' (red line;
>>> ML operating on Gulya's idea), polygenic_hglm (black; Xia/Lars), and
>>> REML.rotate (green; Lars's implementation/extension of Gulya's idea)
>>> as a function of sample size (X axes).
>>> 
>>> While polygenic and hglm show exponential trend, REMLrotate line is
>>> not only the lowest, but also looks almost linear to me (also looking
>>> at the code, it should be roughly linear on time with no of subjects).
>>> So, with REMLrotate we can get arbitrary big speed-up (x100, x1000,
>>> x10000, ... you name it!) cf other methods, just by adding more people
>>> to the data :) Not a bad result!
>>> 
>>> Lars and Gulya, you are the champions!
>>> 
>>> best wishes,
>>> Yurii
>>> 
>>> 2011/5/19 Yurii Aulchenko <yurii.aulchenko at gmail.com>:
>>>> Correction: as Lars spotted out, I did placed my 'tags' wrongly
>>>> concerning time performance results, so actually REML.rotate is the
>>>> fastest.
>>>> 
>>>> Here are updated results:
>>>> 
>>>>> With conv=1e-8 mean time for estimation on 300 IDs was:
>>>>> 
>>>> 17.81 sec for polygenic_hglm
>>>>> 2.27 sec for 'polygenic'-ML
>>>> 1.33 sec for REML.rotate
>>>> 
>>>> best wishes, and sorry for inconvenience,
>>>> Yurii
>>>> 
>>> _______________________________________________
>>> genabel-devel mailing list
>>> genabel-devel at lists.r-forge.r-project.org
>>> https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/genabel-devel
>> 
>> -- 
>> -----------------------------------------------
>> L.C. Karssen
>> Erasmus MC
>> Department of Epidemiology
>> Room Ee-2224
>> 
>> Postbus 2040
>> 3000 CA Rotterdam
>> The Netherlands
>> 
>> phone: +31-10-7044217
>> fax: +31-10-7044657
>> e-mail: l.karssen at erasmusmc.nl
>> GPG key ID: 0E1D39E3
>> -----------------------------------------------
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> 

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