[BioC] SNP Analysis

[Vincent Carey]

For a comparison of crlmm (Bioconductor) and birdseed, see
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2643934/

There are various interfaces between plink and R.  snpMatrix and
SNPchip in Bioconductor should also be considered as one thinks about
workflows for snp arrays.

On Thu, Oct 22, 2009 at 8:51 AM, Peter Ganske <peterganske at mac.com> wrote:
> Dear Claus- Jürgen,
> thanks for the reply. In which way you would analyze the genotype frequency
> wit PLINK?
> And why you use this program instead of any bioconductor- package?
> All the best and thanks in advance
> Peter
>
>
>
> Am 22.10.2009 um 13:13 schrieb Claus-Jürgen Scholz:
>
>>
>> Dear Peter,
>>
>> indeed, Birdseed is a genotyping algorithm and I'd use it for genotype
>> calling of SNP6.0 arrays (best suited for this platform). If you have
>> the calls, export them into a table (export options and formats should
>> be described in the Genotyping Console manual) and analyze the genotype
>> frequency differences between responders and non-responders (valuable
>> free software is e.g. PLINK). However, n=100 is a pretty small sample
>> size for a GWAS...
>>
>> Bests,
>> Claus-Jürgen
>>
>>
>> Peter Ganske schrieb:
>>>
>>> Dear Vincent,
>>> thanks for the fast replay. Well, i thought, that the Genotyping
>>> console used the Birdseed Algorithm and this algorithm is an
>>> Genotyping Algorithm.
>>>
>>> Its hard to find paper or groups, who worked with this array and for
>>> me ( i work as a student for an institue) is hard to find the right
>>> workflow without help (nobody worked here with SNP arrays in the past)
>>>
>>> So, i have 100 Arrays (100 CHP and  100 CEL files) of 100 patients. I
>>> want to have a look at the SNPs of the patients. 50 are non-responder
>>> and 50 are responder. There should be a difference between the two
>>> groups. Since yet, i looked for any papers for getting an "general"
>>> workflow for sorting out most of the SNPs of the patients.
>>>
>>> So you think i have to try this package and create the genotyping calls?
>>> Whats about this workflow? So are my following thought right:
>>>
>>> - The package check every SNP for every Chips and put the result in a
>>> table
>>> - i can combine the result of the SNPs with a selection of gene i
>>> want....
>>>
>>> My boss talked about a top-list of 50 genes... Maybe this can help me
>>> out for the usage of CRLMM.. dont know
>>>
>>> Thanks a lot and sorry for the questions. First time for me to work
>>> with SNP Arrays and the first time to work with Bioconductor/R
>>> All the best from Germany
>>> Peter
>>> Am 21.10.2009 um 16:11 schrieb Vincent Carey:
>>>
>>>
>>>> Briefly, you can perform genotype calling with a confidence measure
>>>> using crlmm package, working from the CEL files.   The crlmm package
>>>> includes a vignette called crlmmDownstream.pdf that illustrates one
>>>> approach to GWAS analysis based on 6.0, using snpMatrix package.  To
>>>> use crlmm you will also need a metadata package called
>>>> genomewidesnp6crlmm.
>>>>
>>>> There are certainly other approaches possible.  Our workflow
>>>> documentation for this use case probably needs some enhancement.
>>>>
>>>> On Wed, Oct 21, 2009 at 9:42 AM, Peter Ganske <Peter.Ganske at hki-jena.de
>>>>
>>>>> wrote:
>>>>>
>>>>> Hello,
>>>>> first time for me to work with SNP arrays. I got CEL- and CHP-files
>>>>> for my Analysis. The CEL are from Affymetrix Human-Wide Genome SNP-
>>>>> Array 6.0 and the CHP- files are dealed with the Birdseed-
>>>>> Algorithm (part of the Genotyp Console from Affymetrix as well).
>>>>> Is there anybody here, who worked with this arrays in the past? I
>>>>> am looking for an (general) workflow for my study. I want to
>>>>> analyse patients with Rheumatoid Arthritis with regard to SNPs and
>>>>> the question "why there are respoonder and non-responder for the
>>>>> therapy"?
>>>>> I am looking for an workflow for the arrays. Is it better to work
>>>>> with the CHP files or with the CEL- files?
>>>>> Would me great, if anybody can help me out.
>>>>> Thanks in advance
>>>>> Peter
>>>>>
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