[BioC] question about limma and gcrma

[James W. MacDonald]

There are two ways to get version numbers.

For a single package:

packageDescription("thepackage")$Version

For all loaded packages:

sessionInfo()

Best,

Jim



Hongqing Li wrote:
> Hi James,
> 
> The whole story is that my hard drive was broken and I only have backup
> files left in csv files and scripts used to generate those files. But I did
> not
> put down the version number of R.gcrma,limma I used, neither could I
> restore the old R working environment, so I have no way to check the
> package.
> versions. I think it is very important to add a line or two on my datafiles
> with
> the version numbers of those packages from now on.
> 
> What I did was simple:
> 
> data<-ReadAffy()
> eset<-gcrma(data)
> exprs2excel(eset,'somefilename')
> 
> When I compare the results from this script and the old one, I can not find
> perfect
> agreement. I installed bioconductor 2.0 last week, so the package should be
> Affy
> 1.14.2, gcrma 2.8.1, limma 2.10.5. as I found out in
> http://www.bioconductor.org/packages/2.0/bioc/
> 
> BTW, how do you print out the version number of a package in R? I googled
> but
> could not find the answer.
> 
> Thanks,
> hongqing
> 
> On 8/23/07, James W. MacDonald <jmacdon at med.umich.edu> wrote:
>> Hi Hongqing,
>>
>> Hongqing Li wrote:
>>> Hi,
>>>
>>> I have been using limma and gcrma for microarray analysis for a while.
>>> recently I have to reinstall my system so I update my R from 2.4 to
>> 2.5.1
>>> I don't know the version of limma,gcrma packages, but they were
>> installed
>>> as I install my old R 2.4.  However, when I run the same script to
>> analyze
>>> the same file I did last year, I got different results for both gcrma
>> and
>>> limma.
>>> Although the difference is not dramatic. I plotted the scatter plot for
>>> gcrma
>>> summarized expression data from old analysis and new analysis, it
>> supposed
>>> to be a straight line, but on my plot the low expression values form a
>>> slightly
>>>  inflated data cloud around the diagonal line. For limma, only about 10
>>> really
>>> large or really small t statistics are strongly different from the old
>>> analysis.
>>> Is this a known issue for using different version of packages ?
>> Well, yes. Probably. Since you don't know what versions you were using,
>> nor the versions you are now using, it is impossible to say for sure
>> (plus you don't say how you are analyzing the data, nor do you give a
>> small reproducible example that we could try ourselves).
>>
>> However, Both limma and gcrma tend to change (limma perhaps more than
>> gcrma) over time, as the maintainers improve both the implementation and
>> underlying statistical methodology, so it is not unlikely that you would
>> get 'not dramatic' changes in results with different versions.
>>
>> Best,
>>
>> Jim
>>> Thanks,
>>> Hongqing
>>>
>>>       [[alternative HTML version deleted]]
>>>
>>> _______________________________________________
>>> Bioconductor mailing list
>>> Bioconductor at stat.math.ethz.ch
>>> https://stat.ethz.ch/mailman/listinfo/bioconductor
>>> Search the archives:
>> http://news.gmane.org/gmane.science.biology.informatics.conductor
>>
>> --
>> James W. MacDonald, M.S.
>> Biostatistician
>> Affymetrix and cDNA Microarray Core
>> University of Michigan Cancer Center
>> 1500 E. Medical Center Drive
>> 7410 CCGC
>> Ann Arbor MI 48109
>> 734-647-5623
>>
> 
> 	[[alternative HTML version deleted]]
> 
> _______________________________________________
> Bioconductor mailing list
> Bioconductor at stat.math.ethz.ch
> https://stat.ethz.ch/mailman/listinfo/bioconductor
> Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor

-- 
James W. MacDonald, M.S.
Biostatistician
Affymetrix and cDNA Microarray Core
University of Michigan Cancer Center
1500 E. Medical Center Drive
7410 CCGC
Ann Arbor MI 48109
734-647-5623