gravatar for Kind Katydid

2 hours ago by

By default, DESingle appears to be written to compare between conditions, so it only does 1:1 tests, inferred from this error message:

Error in DEsingle(counts = [email protected][email protected]@listData$counts, group = [email protected]@listData$seurat_clusters)
Levels number of 'group' is not two

I would like to construct a loop for it to scan through all clusters in a 1:all fashion, just like Seurat's FindAllMarkers function.

Their instructions only show an example of assigning arbitrary numbers of cells into 2 groups:

group <- factor(c(rep(1,50), rep(2,100)))

which isn't very helpful in practice.

Without expertise in R, nor knowing of more elegant solutions, here is a pseudocode to generate n groups, where n = number of clusters, and each group is cluster k:all, then immediately using that group to run DESingle.

cluster_list <- levels([email protected]) # dataset was originally in Seurat format, converted to SCE only for DESingle.

for(cluster in cluster_list) {
      groupname <- paste("group_", cluster, sep="")
      assign(groupname, factor(c([email protected]@listData$seurat_clusters<HELP>, 
      [email protected]@listData$seurat_clusters)))
      clustername <- paste("data_DESingle_cluster_", cluster, sep="")
      assign(clustername, DEsingle(counts = [email protected]@[email protected]$counts, group = groupname))

I'm having trouble implementing that part in <HELP> - how do you use the variable in the for loop (in this case cluster, within the function, and nested within the variable of [email protected]@listData$seurat_clusters?

Alternatively, I'd also very much like to learn about more elegant ways to do this.

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