Download expression matrix with cell cluster information indicated in cell IDs

Feature requests
1

Hi,

Appreciations for Cellenics platform for single cell analysis. After cell clustering and annotation, I would like to do a deconvolution analysis for bulk RNA data to infer cell type proportions. For doing so, I need a single cell expression matrix as a reference. The current Cellenics can export an expression matrix. However, the output matrix does not indicate any metadata information in the cell ID. It’s something like “GGGACCTGTCATTGCA-1_3”, which from my understanding should be the sequencing index of the cell. What would be more useful for a cell ID I think, may be something like “Cluster1_sample2.cell3”. Will it be possible to download expression matrix with metadata indicated? Also, what normalisation method has been applied to the matrix data? The deconvolution method I am trying to use recommend the sc data not to be log transformed. I am wondering if more options can be added to the feature of the output expression matrix.

More specifically, I am using the “AutoGeneS” package to do deconvolution. The required input of the single cell data reference is an expression matrix featuring different cell types. Each row of the matrix file is a gene. The whole matrix contains about 4000 highly variable genes. Each column of the matrix is a cell type. Each value in the matrix is the normalised mean expression count of a cell type for each gene.

Thanks for any advices!

Best wishes,
Hongxin

2

Hi Hongxin,
Apologies for the late reply, your message seems to have slipped through the cracks. Thank you for your appreciation of the platform!
Regarding your request, the exported expression matrix from Cellenics includes cell IDs such as “GGGACCTGTCATTGCA-1_3”, which indeed correspond to unique sequencing indexes. Unfortunately, it is currently not possible to download an expression matrix with metadata from Cellenics/Trailmaker. The expression matrix you can export is log-normalized, which may not be suitable for your deconvolution analysis with AutoGeneS.

If you need raw counts with metadata, I suggest downloading the Seurat object from Cellenics/Trailmaker. You can extract the raw count matrix, which is located in the slot scdata@assays$RNA@counts, and process it by adding the required metadata found in the slot scdata@meta.data. This task is best performed in RStudio, as it goes beyond the platform’s current capabilities.

We appreciate your feedback and will consider these suggestions for future development.