Integrated Dimension Reduction Plot for CD4/CD8 sorted Feedback

Hello,

I have recently followed adopted the Harvard Chan Bioinformatics Core guidelines for SC QC/Normalization/Clustering (hbctraining.github.io/scRNA-seq_online/schedule/links-to-lessons.html). I have integrated CD4+/CD8+ T cells from two time points.

I recently received feedback that my integrated dimension reduction plot clustering looked problematic. Specifically, the small clusters peripheral (splash/star?) and the number of distinct clusters.

Data was normalized using SCTransform, variables regressed were mitochondrial ratio and G2M-S phase score difference, as suggested for differentiating cell types. Alternative Workflow: satijalab.org/seurat/articles/cell_cycle_vignette.html

My clusters were called at 40 PC’s w/ 0.6 resolution.

As for the number of clusters, TCR B VDJ subgenes were identified as strong conserved markers in several clusters. I wonder if it is worth excluding VDJ markers from analysis?

Any comment on the appearance of the dim plot and implications would be appreciated. Thank you!

To me the sporadic clustering reminds me of using clonotype edit distance for dimensional reduction – I would consider removing the TCR genes not from the anchoring, but from the runUMAP() call. Below is an example of the problem I encountered trying to convert TCR edit disance into an assay for a Seurat Object.

You can do this with:

quietTCRgenes <- function(sc) {
    unwanted_genes <- "TRBV*|^TRBD*|^TRBJ*|^TRDV*|^TRDD*|^TRDJ*|^TRAV*|^TRAJ*|^TRGV*|^TRGJ*"
    if (inherits(x=sc, what ="Seurat")) {
        unwanted_genes <- grep(pattern = unwanted_genes, x = sc[["RNA"]]@var.features, value = T)
        sc[["RNA"]]@var.features <- sc[["RNA"]]@var.features[sc[["RNA"]]@var.features %!in% unwanted_genes]
    } else {
        #Biocondutor scran pipelines uses vector of variable genes for DR
        unwanted_genes <- grep(pattern = unwanted_genes, x = sc, value = T)
        sc <- sc[sc %!in% unwanted_genes]
    }
    return(sc)
}

seuratObj <- quietTCRgenes(seuratObj)