scRNA profiles from multiple time points; Seurat to URD; clustering in Seurat about urd

[chiblyaa]

Hi Stephen,

I updated Jeffrey's SeuratToURD function to import the Seurat (v3) object into URD. I'm just testing it now and haven't encountered any issues so far. You'll have to create a custom function - in this case I named it seuratToURD2 - and then use that one to import your seurat object. Here's the code:

seuratToURD2 <- function(seurat.object) {
  if (requireNamespace("Seurat", quietly = TRUE)) {
    # Create an empty URD object
    ds <- new("URD")
    
    # Copy over data
    [email protected] <- as(as.matrix(seurat.object@assays$RNA@data), "dgCMatrix")
    if(!any(dim(seurat.object@assays$RNA@counts) == 0)) [email protected] <- as(as.matrix(seurat.object@assays$RNA@counts[rownames(seurat.object@assays$RNA@data), colnames(seurat.object@assays$RNA@data)]), "dgCMatrix")
    
    # Copy over metadata
    ## TO DO - grab kmeans clustering info
    get.data <- NULL
    if (.hasSlot(seurat.object, "data.info")) { 
      get.data <- as.data.frame(seurat.object@[email protected])
    } else if (.hasSlot(seurat.object, "meta.data")) { 
      get.data <- as.data.frame([email protected]) 
    }
    if(!is.null(get.data)) {
      di <- colnames(get.data)
      m <- grep("res|cluster|Res|Cluster", di, value=T, invert = T) # Put as metadata if it's not the result of a clustering.
      discrete <- apply(get.data, 2, function(x) length(unique(x)) / length(x))
      gi <- di[which(discrete <= 0.015)]
      ds@meta <- get.data[,m,drop=F]
      [email protected] <- get.data[,gi,drop=F]
    }
    
    # Copy over var.genes
    if(length(seurat.object@[email protected] > 0)) [email protected] <- seurat.object@[email protected]
    
    # Move over tSNE projection
    if (.hasSlot(seurat.object, "tsne.rot")) {
      if(!any(dim([email protected]) == 0)) {
        [email protected] <- as.data.frame([email protected])
        colnames([email protected]) <- c("tSNE1", "tSNE2")
      }
    } else if (.hasSlot(seurat.object, "reductions")) {
      if(("tsne" %in% names(seurat.object@reductions)) && !any(dim(seurat.object@reductions$tsne) == 0)) {
        [email protected] <- as.data.frame(seurat.object@[email protected])
        colnames([email protected]) <- c("tSNE1", "tSNE2")
      }
    }
    
    # Move over PCA results
    if (.hasSlot(seurat.object, "pca.x")) {
      if(!any(dim([email protected]) == 0)) {
        [email protected] <- [email protected]
        [email protected] <- [email protected]
        warning("Need to set which PCs are significant in @pca.sig")
      }
      ## TO DO: Convert SVD to sdev
    } else if (.hasSlot(seurat.object, "reductions")) {
      if(("pca" %in% names(seurat.object@reductions)) && !any(dim(Loadings(seurat.object, reduction = "pca")) == 0)) {
        [email protected] <- as.data.frame(Loadings(seurat.object, reduction = "pca"))
        [email protected] <- as.data.frame(seurat.object@[email protected])
        [email protected] <- seurat.object@reductions$pca@stdev
        [email protected] <- pcaMarchenkoPastur(M=dim([email protected])[1], N=dim([email protected])[1], [email protected])
      }
    }
    return(ds)
  } else {
    stop("Package Seurat is required for this function. To install: install.packages('Seurat')\n")
  }
}

[farrellja]

There is a function seuratToURD that should work with Seurat v2. I have not yet updated it for Seurat v3, and I believe the structure of the object changed there. You would then need to do all steps beginning with Calculate Diffusion Map in the QuickStart tutorial. The method that URD uses to calculate variable genes is different from Seurat, so you may also want to explore URD's variable gene results and compare them to those from Seurat. Additionally, if you didn't calculate a tSNE representation in Seurat, you may want to calculate one in URD just for visualization and exploration. Clustering wise, I generally cluster at each stage individually, though you could try exploring both methods.

[farrellja]

Thanks, Augustin! I will incorporate this into the code base soon & add an acknowledgment to you in the documentation & homepage.

[CLambert7]

Thanks Stephen - really helpful!