I am trying STACAS on my 12 samples Seurat data obj, scdata.Each sample is preprocessed (i.e. QCd, filtered and normalized).
The range for the N of cells in the samples is [245, 8958].
The range for the N of features in the RNA assay in the samples is [16900, 27554]
When I try to integrate using
scdata.combined <- Run.STACAS(scdata, dims = 1:nPCs, anchor.features = intfeatures, new.assay.name = "stacas")
where intfeatures results from SelectIntegrationFeatures and is a vector of ~3000 elements
I get the following error :
Integrating dataset 4 with reference dataset
Error in GetAssayData(object = object, assay = umi.assay, slot = "counts")[features_to_compute, :
no 'dimnames' attribute for array
Same error if I set anchor.features = 3000
As far as I understand this probably is because the AssayData is an empty matrix, which I assume it is because features_to_compute may be an empty vector.
I am not sure why this is happening. o you have any suggestions ?
Hi,
I am trying STACAS on my 12 samples Seurat data obj, scdata.Each sample is preprocessed (i.e. QCd, filtered and normalized). The range for the N of cells in the samples is [245, 8958]. The range for the N of features in the RNA assay in the samples is [16900, 27554]
When I try to integrate using scdata.combined <- Run.STACAS(scdata, dims = 1:nPCs, anchor.features = intfeatures, new.assay.name = "stacas") where intfeatures results from SelectIntegrationFeatures and is a vector of ~3000 elements
I get the following error : Integrating dataset 4 with reference dataset Error in GetAssayData(object = object, assay = umi.assay, slot = "counts")[features_to_compute, : no 'dimnames' attribute for array
Same error if I set anchor.features = 3000
As far as I understand this probably is because the AssayData is an empty matrix, which I assume it is because features_to_compute may be an empty vector.
I am not sure why this is happening. o you have any suggestions ?
Thanks