Seurat v5使用IntegrateLayers功能实现了简化的整合分析。该方法目前支持五种整合方法。每一种方法都在低维空间中执行整合,并返回降维结果(例如integrated.rpca): Anchor-based CCA integration (method=CCAIntegration) Anchor-based RPCA integration (method=RPCAIntegration) Harmony (method=HarmonyIntegration) FastMNN ...
("./data/umi_counts/Pancreas_datasets/Muraro/")Muraro_obj<-CreateSeuratObject(Muraro)Muraro_obj$dataset<-"Muraro"obj<-merge(Baron_obj,Muraro_obj)obj<-NormalizeData(obj)|>FindVariableFeatures(selection.method="vst",nfeatures=2000)obj<-ScaleData(obj)obj<-RunPCA(obj)obj<-IntegrateLayers(object=...
@@ -1322,8 +1377,8 @@ RowMergeSparseMatrices <- function(mat1, mat2) { all.mat <- lapply(X = all.mat, FUN = as, Class = "RsparseMatrix") all.names <- unique(x = do.call(what = c, args = all.rownames)) new.mat <- RowMergeMatricesList( mat_list = all.mat, mat_ro...
then you don't need to perform integration. If you just want to combine two Seurat objects without any additional adjustments, there amergefunction anda vignette for that workflow.
Hi, @BridgeLeeH Maybe you can merge the small objects into the bigger one. liu-xingliang mentioned this issue Dec 16, 2021 IntegrateData() : Could I integrate seurat dataset with different cell numbers (from 100 to 5000)? And an Error: Error in idx[i, ] <- res[[i]][[1]] : ...