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yunzhang813 / FUNNEL-GSEA-R-Package

Zhang et al. 2017. FUNNEL-GSEA: FUNctioNal ELastic-net regression in time-course gene set enrichment analysis. Bioinformatics, 33(13), 1944-1952.
https://doi.org/10.1093/bioinformatics/btx104
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using FUNNEL for single cell data #3

Open qvhaelen opened 5 years ago

qvhaelen commented 5 years ago

Hello,

I have another quick question regarding the use of the method FUNNEl. Is the algorithm suitable for single cell data ( analysis is the study of transcriptomics at the single cell level.)?

thank you

best regards

Quentin

yunzhang813 commented 5 years ago

Hi Quentin,

Regarding to the single cell RNA-seq data, we have not tested it on single cell gene expressions yet. The functional data analysis techniques we employed in FUNNEL (e.g. fPCA; fRegression) and the data transformation techniques (i.e., turn fRegression into multivariate regression via covariance matrix decomposition) depends on the normality assumption. So if the single cell expression data is too far from being “normal”, you cannot directly apply our method. In principle, it should be doable to find a data transformation that matches the log-likelihood function of the single cell data distribution and the multivariate log-likelihood function.

Best, Yun

From: qvhaelen notifications@github.com Reply-To: yunzhang813/FUNNEL-GSEA-R-Package reply@reply.github.com Date: Wednesday, September 26, 2018 at 4:39 AM To: yunzhang813/FUNNEL-GSEA-R-Package FUNNEL-GSEA-R-Package@noreply.github.com Cc: Subscribed subscribed@noreply.github.com Subject: [yunzhang813/FUNNEL-GSEA-R-Package] using FUNNEL for single cell data (#3)

Hello,

I have another quick question regarding the use of the method FUNNEl. Is the algorithm suitable for single cell data ( analysis is the study of transcriptomics at the single cell level.)?

thank you

best regards

Quentin

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