Hello everyone,
I have a multi-ome data, and used scenicplus to identify different TF enrichment in my cell type, and I was wondering if it possibille to check the different enhancers that TF bind to, in the different cell type.
Hello everyone, I’m annotating cells from VisiumHD samples that I recently received. The quality of the samples is quite low in terms of the total number of counts and the number of genes detected by the cells. As a result, I was unable to reliably identify around 30 to 65% of the cells. When I looked closer, I discovered that these cells mostly express unique markers. For instance, one cluster expresses a unique marker of Cell Type A, while another cluster expresses another marker of Cell Type A, even though biologically, these markers should be expressed in the same cells (the differences is driven by noise and low number of UMIs). Additionally, most genes have only around one transcript. I’m wondering if this could be a problem during peer review and if it makes sense to annotate them in this way by just assigning a label regardless of depth if that marker is unique when cross referencing with single cell dataset.