[BioC] Does old workspace work?

[Kasper Daniel Hansen]

On Nov 10, 2008, at 11:50 , Loren Engrav wrote:

> So I fixed up the old workspace from early 2007 with all your help
> Installed 64bit Intel MacOS stuff
> Installed the new BioC maanova stuff
> Changed one of the 60 chips
> And reran the mixed linear regression previously done in early 2007
> The command was
>
> ftest.Breed.mix_1000perm081109 <- matest
> (BDeset_gcrma_NoCon25LRmadata.raw.WithAffyID081109,  
> BGanova.Br_T.mix081109,
> term = “Breed”, n.perm = 1000, critical = .9, test.type = c("ftest"),
> shuffle.method = c("sample"), MME.method = c("REML"), test.method =
> c(1,0,1,1), pval.pool = TRUE, verbose = TRUE)
>
> In early 2007 this process took about 40 hours
> This time it took 15 hours which is a serious improvement
>
> Four derivative questions Please
> #1I noticed the computer was using only one of the 8 processors
> Can R/BioC use all of the processors?

In general R is single threaded, so no. However, on Mac OS, R is  
(typically) build against "Altivec" which is an Apple supplied,  
multithreaded version of BLAS and Lapack. What this means is that any  
computation that involves matrix algebra, will use all your cores.  
This could very well be behind the substantial speed up you see. It is  
also possible to make packages utilize multiple cores, but this is  
somewhat non-standard and hard to do. One example is affypara, for  
preprocessing of affy arrays.

> I received this warning many many times
> 50: In any(parsed.formula$random) ... : coercing argument of type  
> 'double'
> to logical
> #2Is this significant?

I have no idea.

> I have 64bit R.app but to install the 64bit packages I quit R.app  
> and in
> terminal do
> source ("http://www.bioconductor.org/biocLite.R")
> biocLite (c("whatever"), type="source")
> It seems I cannot install the 64bit packages from R.app
> #3Is this true? This has been discussed but I cannot find the  
> definitive
> skinny

If you are using Mac OS X on an Intel machine, the latest Bioconductor  
builds includes 64bit versions. So that means that type = "mac.binary"  
should give you a 64 bit version.

Whether or not you do this from R.app should not have any impact.

> In the old workspace there are several objects like
> "biocinstall.defaultPkgs"
> "biocinstall.graphPkgs"
> "biocinstall.litePkgs"
> which are scripts of various types I guess to install groups of  
> packages,
> like
>
> function()
> {
>        contriburl = "http://bioconductor.org/packages/1.9/bioc/src/contrib 
> "
>        available.packages(contriburl)[, "Package"]
> }
>
> #4Are these scripts old and no longer used to install groups?

These scripts are by-product of doing
R> source(http://www.bioconductor.org/biocLite.R")
and can safely be deleted. They will be recreated, if necessary,  
everytime you source biocLite.

Kasper

> Thank you again
>
>> From: Loren Engrav <engrav at u.washington.edu>
>> Date: Fri, 31 Oct 2008 15:38:12 -0700
>> To: "bioconductor at stat.math.ethz.ch" <bioconductor at stat.math.ethz.ch>
>> Subject: Re: [BioC] Does old workspace work?
>>
>> Cool, I can deal with evolution
>>
>> And the archives will be a super addition to ? and google, thank  
>> you, maybe
>> better than google
>>
>> So we biopsied shallow and deep wounds on 3 Duroc pigs and 3  
>> Yorkshire pigs
>> at 1 2 3 12 and 20 weeks, this then is 60 porcine chips with 24123  
>> probe
>> sets on the chip, we were interested in chip2-chip1, chip4-chip3, etc
>> And studied the differences with R/maanova and various biologic data
>> reduction steps to achieve a group of 1289 for further study
>>
>> So for the fun of it,  I compared chip2-chip1 in gcrmaOld and  
>> gcrmaNew
>>
>> In gcrmaOld there were no differences of exactly zero
>> In gcrmaNew 249/24123 were exactly zero which seems kinda funny
>> This affected 4 in the group of 1289 but did not change anything
>>
>> 9247/24123 differences changed sign which is potentially bad for  
>> this study;
>> but after cutting those with log ratio < .5 as too trivial to worry  
>> about in
>> this complex system, zero were left
>>
>> I could rerun this, but given this, and that the old Mac PRO PPC  
>> took ~40
>> hours to run the mixed linear regression, I think the old data is  
>> just fine
>>
>> And since
>> objNew <- as(objOld, "ExpressionSet") works would appear I am back in
>> business
>>
>> Thank you all
>>
>>
>> From: Sean Davis <sdavis2 at mail.nih.gov>
>> Date: Fri, 31 Oct 2008 15:00:47 -0400
>> To: Loren Engrav <engrav at u.washington.edu>
>> Cc: "bioconductor at stat.math.ethz.ch" <bioconductor at stat.math.ethz.ch>
>> Subject: Re: [BioC] Does old workspace work?
>>
>>
>>
>> On Fri, Oct 31, 2008 at 2:47 PM, Loren Engrav <engrav at u.washington.edu 
>> >
>> wrote:
>>> Thank you, got it
>>>
>>> exprs(obj) is missing from the output but shows in ?ExpressionSet  
>>> and puts
>>> up the data so I can see it
>>>
>>> And now perhaps one final question to understanding this old data  
>>> and
>>> progress
>>>
>>> Long long ago I did
>>> AA_ReadAffy <- ReadAffy()
>>> ABeset_gcrma < gcrma (AA_ReadAffy)
>>>
>>> Now I do
>>> AA_ReadAffy081031 <- ReadAffy() #on the same .cel files
>>> ABeset_gcrma081031 <- gcrma (AA_ReadAffy081031)
>>>
>>> Then I do
>>> Show(ABeset_gcrma) and exprs(ABeset_gcrma081031)
>>>
>>> And they do not match, for example
>>> Probe set Ssc.10026.1.A1_at
>>> ABeset_gcrma is 4.124689
>>> ABeset_gcrma081031 is 3.344443
>>>
>>> ReadAffy changed?
>>> gcrma changed?
>>
>> See:
>>
>> http://thread.gmane.org/gmane.science.biology.informatics.conductor/16664/fo
>> cus=16664
>>
>> The bioconductor archive is your friend.
>>
>> Sean
>>
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>
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