[R-sig-genetics] R-sig-genetics Digest, Vol 8, Issue 2

Brad McNeney mcneney at cs.sfu.ca
Sat Sep 11 01:54:46 CEST 2010


Hi Ross,

Thanks for this.  I take it then that the QC tools you have in Galaxy 
are not in any of the Bioconductor Genetics{Base,Design,Ped} packages? 
If not, are there plans to update the Bioconductor packages?

Cheers,

Brad
---
Brad McNeney
Statistics and Actuarial Science
Simon Fraser University

On 10/09/2010 11:51 AM, Ross wrote:
> Hi, Fernando,
>
> I think there are some QC tools in David Clayton's snpMatrix package,
> but there's no single R package to do all the reports you need AFAIK.
> For comprehensive reporting, if you don't mind not using R, one option
> is to try the SNP/WGA tools in Galaxy - they do use R for graphics but
> you don't need to install anything as it all works through an ordinary
> web browser.
>
> Essentially, if you have your genotype and pedigree data in Plink
> style linkage format (separate map and ped files), the steps are
> something like this:
>
> 1. make yourself a new user account at the main Galaxy server
> (http://usegalaxy.org) so your histories are preserved between logins
>
> 2. From the analysis window, left (tool) pane, click the Get Data tool
> group header to expand the group, then click the 'upload file' tool.
> A form will appear in the center pane of your browser.
>
> 3. Change the file format (first field on the form) from Auto to
> "lped" format as autodetect won't work for these multi-part datatypes
> 4. Make the 'ped' and 'map' file upload fields point to the right map
> and ped files on your local machine, set the 'build' to hg18 and
> change the name to reflect something informative about your data then
> click execute.
>
> 5. After the data are uploaded (should only take a minute or two for a
> small file) to your history, you can select the SNP/WGA QC LD Plots
> tool submenu in the tool pane and then click the QC tool. Another form
> will open in the center panel. Your new dataset should be the only one
> available in the drop-down list of files to process. Change the QC job
> name to a meaningful name, click 'execute'. For a small dataset, the
> whole process should run for a few minutes but you can safely log out
> and log back in later - your work will all be preserved.
>
> 6. The QC tool output (in the right side history pane) has an 'eye'
> icon which you can click to open up the report in the center panel -
> you should see HWE/missingness/Mendel and all sorts of other useful
> plots and there are some tabular files containing summary details by
> marker and by sample.
>
> I'm happy to answer any questions you might have - I hope this helps
> get you started?
>
> There's a 'clean' tool you can use to remove markers and subjects that
> fall below specific thresholds for QC measures and there's a TDT tool
> you can use for analysis of family data.
>
>
> On Fri, Sep 10, 2010 at 6:00 AM,<r-sig-genetics-request at r-project.org>  wrote:
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>> Today's Topics:
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>>    1. Available R packages to QC/summarize large SNP    datasets?
>>       (GRIGNOLA, FERNANDO E [AG/1000])
>>
>>
>> ----------------------------------------------------------------------
>>
>> Message: 1
>> Date: Thu, 9 Sep 2010 10:54:23 -0500
>> From: "GRIGNOLA, FERNANDO E [AG/1000]"
>>         <fernando.e.grignola at monsanto.com>
>> To:<r-sig-genetics at r-project.org>
>> Subject: [R-sig-genetics] Available R packages to QC/summarize large
>>         SNP     datasets?
>> Message-ID:
>>         <2335BBF3D6579746A3165D5D7B95DF7018D1BB at NA1000EXM12.na.ds.monsanto.com>
>>
>> Content-Type: text/plain; charset="us-ascii"
>>
>> Hi,
>>
>> I looking for some guidance regarding available packages to do QC (i.e.
>> parent-offspring inheritance checks) and to summarize large SNP datasets
>> (i.e. 50K) for pedigreed populations (frequencies, linkage calculations,
>> etc).
>>
>> I know of some packages that check for HW equilibrium, get frequencies
>> as part of the data preparation for genome-wide association analyses for
>> example. However, I was wondering if somebody can point me to 1 or 2
>> packages that mostly focus on data quality and summary statistics for
>> large SNPs of data.
>>
>> Thanks in advance for your assistance,
>>
>>
>>
>> Fernando
>>
>>
>>
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