[Bioc-devel] Class for differentially expressed genes?

[Roman Hillje]

Thank you for the responses so far!

The idea behind this is that I don’t want to limit users to a certain DGE toolkit, may it be DESeq2, edgeR or frameworks specifically developed for single cell data such as muscat. I’d like to have a common structure that users can pour their results into (most variables are probably generated by all methods), which ensures that it matches a certain format. Then, I can build the visualisation in a Shiny app around that format. I could just make my own format but I want to avoid complicated explanations of how the data frame must look like to be in the correct format. Also, knowing myself, if I have control over the format, I might get tempted to change it in the future resulting in compatibility issues...

Regarding the SummarizedExperiment class: Would you suggest leaving most of the object empty and use the feature info slot (accessible through “rowData()”)? From the vignette it looks like that's just a normal data frame.

I’ll keep exploring.

Best,
Roman

> On 9. Mar 2020, at 13:02, Constantin Ahlmann-Eltze <constantin.ahlmann using gmail.com> wrote:
> 
> Hi Roman,
> 
> I think it is probably also helpful to check out how DESeq2 and edgeR 
> (two popular Bioconductor packages for differential expression analysis) 
> have solved that problem:
> 
> In DESeq2 for example the `nbinomWaldTest()` function calculates the 
> differential expression and stores the results in the `rowData()` of the 
> DESeqDataSet / SummarizedExperiment. The `results()` function extracts a 
> standard `data.frame` with all the columns that you mentioned.
> 
> In edgeR the `glmLRT()` function calculates differential expression with 
> the likelihood ratio test and returns directly a `data.frame` with the 
> mentioned columns.
> 
> Best Regards,
> Constantin
> 
> Am 09.03.20 um 12:44 schrieb Shepherd, Lori:
>> I would imagine a SummarizedExperiment would be the best option
>> https://bioconductor.org/packages/release/bioc/html/SummarizedExperiment.html
>> 
>> 
>> 
>> 
>> Lori Shepherd
>> 
>> Bioconductor Core Team
>> 
>> Roswell Park Comprehensive Cancer Center
>> 
>> Department of Biostatistics & Bioinformatics
>> 
>> Elm & Carlton Streets
>> 
>> Buffalo, New York 14263
>> 
>> ________________________________
>> From: Bioc-devel <bioc-devel-bounces using r-project.org> on behalf of Roman Hillje via Bioc-devel <bioc-devel using r-project.org>
>> Sent: Monday, March 9, 2020 6:48 AM
>> To: bioc-devel using r-project.org <bioc-devel using r-project.org>
>> Subject: [Bioc-devel] Class for differentially expressed genes?
>> 
>> Hi all,
>> 
>> I was wondering if there is a class for results of differential gene expression analysis. I couldn�t find anything generic. Perhaps it�s too similar to a simple data frame, but I like the idea of having a consistent format. I would imagine something that holds gene names, statistics (logFC, p-value, adjusted p-value), plus optional information, e.g. the percent of cells expressing a gene (in the context of scRNA-seq). This could then be attached to an SCE object (�metadata" slot) to keep all results together. I�m probably making things too complicated and should just use a simple data frame but wanted to be sure that I�m not missing any existing solution. I�d appreciate if you share your advice. Thank you!
>> 
>> Cheers,
>> Roman
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