[Bioc-devel] Modeling (statistic, p-value) pairs in MultiAssayExperiment

[Francesco Napolitano]

I'm converting gene expression profiles to "pathway expression
profiles" (https://doi.org/10.1093/bioinformatics/btv536), so for each
pathway I have an enrichment score and a p-value. I guess it would be
like modeling gene expression data where limma-like preprocessing was
performed, so you have a fold change - p-value pair for each gene.
Isn't there a data model for that?

thanks,
Francesco


On Tue, Oct 24, 2017 at 3:15 AM, Kasper Daniel Hansen
<kasperdanielhansen at gmail.com> wrote:
> Are you discussing statistics of the same dimension as the data (unusual) or
> summary statistics? We should think about a MAE version of summary
> statistics, but that is not captured in current representation I would say.
>
> Best,
> Kasper
>
> On Mon, Oct 23, 2017 at 4:50 PM, Vincent Carey <stvjc at channing.harvard.edu>
> wrote:
>>
>> no answers yet?  would it work to put your matrices as separate assays in
>> a
>> SummarizedExperiment?
>> as long as they are conformant in dimensions and dimnames I think that
>> would work.  That
>> SummarizedExperiment would then work well in an MAE.
>>
>> On Mon, Oct 23, 2017 at 1:00 PM, Francesco Napolitano
>> <franapoli at gmail.com>
>> wrote:
>>
>> > Hi,
>> >
>> > I'm trying to build a MultiAssayExperiment. However, in my case each
>> > assay should ideally include two matrices: one with a statistic and
>> > another one with the corresponding p-value. I'm currently managing
>> > each of them simply as a list of two matrices, but assay class expects
>> > table-like data. I must also be able to quickly extract entire rows or
>> > columns from each matrix.
>> >
>> > Is there a suitable way to model this into a MultiAssayExperiment?
>> >
>> > Thank you,
>> > Francesco
>> >
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