Running reactomeGSA on multiple resolution cluster separately

[Ankita-1211]

Hi

Thank you for helping me running reactomeGSA for pathway analysis.

I need lil help in understanding this.

The seurat-result.rds file I am using is having multiple resolution cluster information.

my seurat@metadata look like this

<style> </style>

	orig.ident	nCount_RNA	nFeature_RNA	percent.mt	nCount_SCT	nFeature_SCT	SCT_snn_res.0.1	seurat_clusters	SCT_snn_res.0.2	SCT_snn_res.0.3	SCT_snn_res.0.4	SCT_snn_res.0.5	SCT_snn_res.0.6	SCT_snn_res.0.7	SCT_snn_res.0.8	SCT_snn_res.0.9	SCT_snn_res.1.0	SCT_snn_res.1.1	SCT_snn_res.1.2	SCT_snn_res.1.3	SCT_snn_res.1.4	SCT_snn_res.1.5
AACACACTCGACGAGA	SeuratProject	4462	2071	0.054459883	6629	2093	0	2	1	1	1	1	1	0	0	0	0	0	0	0	2	2
AACAGGGTCAGAATAG	SeuratProject	19959	4112	0.091838268	8600	2649	0	3	1	1	1	1	1	0	0	0	0	0	0	0	4	4

how can I used this seurat cluster file for running reactomeGSA on each single resolution one by one.

So far when I try to set the indents as Idents(object = data) <- "SCT_snn_res.0.8"

and then running gsva_result <- analyse_sc_clusters(seuset, verbose = TRUE)
it gives me error Error: Only one identification found: 'integrated_snn_res.0.8'. Please ensure that cell / cluster ids are stored as the primary identification (Ident) of your Seurat object. Clustering has to be performed prior to this pathway analysis.

Could you pls guide me in running the reactomeGSA for each resolution cluster separately?

[jgriss]

Dear @Ankita-1211 ,

You can find detailed instructions on how to work with Seurat objects in the Seurat documentation.

Your code sets the identification of all cells to "SCT_snn_res.0.8" (the actual string).

What you rather want is setting it to the clustering results using

Idents(object = data) <- data$`SCT_snn_res.0.8`

That way, the values of the SCT_snn_res.0.8 slot are used as the cell identifiers.

Kind regards,
Johannes