Thanks Jim. I will try the packages you suggested. Really appreciate your
help.

best,
Xiaowei

On Mon, Jan 3, 2011 at 1:00 PM, James W. MacDonald <jmacdon@med.umich.edu>wrote:

> Hi Xiaowei,
>
>
> On 12/30/2010 12:55 PM, Xiaowei Guan wrote:
>
>> Dear Bioconudctor,
>>
>> I have this question about how to compress the gene expression dataset
>> from
>> probe sets denoted to gene denoted values.
>>
>> The analysis has two simultaneous goals, first is to convert the probe
>> sets
>> to gene names. Second is to convert the probe sets values into just one
>> summary gene expression value of the associated gene.
>>
>>  For example, we have 21 probes that corresponding to only 4 genes, Is
>> there
>> any package will fulfill the goal of deriving a summary information of a
>> probe set corresponding to a specific gene?
>>
>
> You are not using very exacting language here. If I assume you are using
> Affymetrix chips, then a probe is quite different from a probe set. If I
> further assume that any time you say 'probe' you actually mean probe set
> (e.g., 'we have 21 probe [sets] that correspond to only 4 genes'), then
> there are a couple of ways you can go here. And each has its own positive
> and negative aspects.
>
> You could use one of the MBNI re-mapped CDF packages, which map the probes
> to (genes, transcripts, etc, depending on the package), so each probe set
> uniquely measures a single entity. The positive aspects of these CDF
> packages is that you no longer have multiple probesets for each gene. The
> negative aspect is that the number of probes per probe set is highly
> variable, so the accuracy of the measurements will vary as well (and this is
> usually not accounted for when doing downstream analyses).
>
> Alternatively, you could choose just one probe set for each gene, based on
> something like the most variability between your sample types, or the
> largest difference. There is a function findLargest() in the genefilter
> package that can help, and there may be others as well. The positives for
> this approach are that you again only have one probe set per gene. The
> negative is that you are making the (unfounded IMO) assumption that you can
> determine which probe set is measuring a given gene on such a simple
> criterion.
>
>
>
>> Another question is: if there are no gene assignments for our data (only
>> probes names here),is there any way to assign the genes to each probe
>> simultaneous when getting the summary information of the probe set? When
>> download the annotation file. I noticed there are some probes which have
>> two
>> or more gene names, and in such case, we want to have two same columns
>> with
>> different gene names.
>>
>
> If there are no gene assignments to a probe set, that is because it likely
> doesn't measure any transcript. Most of the Affy chips were designed years
> ago, and given the fluid nature of gene annotations it isn't unusual for
> some of them to no longer be considered to measure a known gene.
>
> As for your second question, that's easy. Just make another row and tack on
> the second gene name. It's probably not advisable, however. In these cases
> you aren't sure what the probe set is measuring, so attributing the data to
> two genes is a fairly risky proposition.
>
> Best,
>
> Jim
>
>
> Thank you so much!
>
>>
>> Best,
>> Xiaowei
>>
>>        [[alternative HTML version deleted]]
>>
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>
> --
> James W. MacDonald, M.S.
> Biostatistician
> Douglas Lab
> University of Michigan
> Department of Human Genetics
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