{"id":66559,"date":"2026-11-15T22:15:00","date_gmt":"2026-11-15T14:15:00","guid":{"rendered":"https:\/\/www.biocloudservice.com\/wordpress\/?p=66559"},"modified":"2026-11-15T14:01:11","modified_gmt":"2026-11-15T06:01:11","slug":"rental-q017-a","status":"publish","type":"post","link":"https:\/\/www.biocloudservice.com\/wordpress\/rental-q017-a\/","title":{"rendered":"\u7528\u78c1\u76d8\u540e\u7aef\u4e0esketch\u7b56\u7565\u642d\u5efa\u5927\u89c4\u6a21\u5206\u6790\u6d41\u7a0b"},"content":{"rendered":"

<\/p>\n

\n
\"\u5b8c\u6574\u6570\u636e\u7559\u76d8\uff0c\u660e\u786e\u54ea\u4e9b\u6b65\u9aa4\u62bd\u6837\uff1a\u5efa\u7acb\u53ef\u6838\u5bf9\u7684\u78c1\u76d8counts\uff1b\u5728sketch\u4e0a\u5b66\u4e60\u8868\u793a\uff1b\u6309\u76ee\u6807\u6295\u5f71\u5230\u5168\u91cf\uff1b\u6253\u5305\u540e\u7aef\u5e76\u590d\u9a8c\u8bfb\u53d6\"
\u672c\u6587\u64cd\u4f5c\u4e0e\u68c0\u67e5\u8def\u5f84\u793a\u610f\u3002<\/figcaption><\/figure>\n

\u9762\u5bf9\u51e0\u5341\u4e07\u7ec6\u80de\uff0c\u9996\u5148\u8981\u533a\u5206\u201c\u4fdd\u7559\u5b8c\u6574\u8868\u8fbe\u6570\u636e\u201d\u4e0e\u201c\u6bcf\u4e00\u6b65\u90fd\u5728\u5b8c\u6574\u6570\u636e\u4e0a\u8ba1\u7b97\u201d\u3002Seurat\u7684\u78c1\u76d8\u77e9\u9635\u4e0esketch\u6d41\u7a0b\u63d0\u4f9b\u4e00\u79cd\u53ef\u9009\u8def\u5f84\uff1a\u5b8c\u6574counts\u7559\u5728\u78c1\u76d8\uff0c\u9009\u5b9a\u7ec6\u80de\u7528\u4e8e\u90e8\u5206\u63a2\u7d22\uff0c\u518d\u628a\u5b66\u5230\u7684\u8868\u793a\u6216\u6807\u7b7e\u6295\u5f71\u5230\u5168\u91cf\u6570\u636e\u3002\u5b83\u4e0d\u662f\u628a\u5927\u4efb\u52a1\u81ea\u52a8\u53d8\u6210\u5b8c\u5168\u65e0\u5185\u5b58\u9700\u6c42\u7684\u64cd\u4f5c\u3002<\/p>\n

\u4e0b\u9762\u6f14\u793a\u5f53\u524d\u516c\u5f00\u5de5\u4f5c\u6d41\uff0c\u8981\u6c42Seurat\u3001SeuratObject\u548cBPCells\u517c\u5bb9\uff0c\u4fdd\u5b58\u8f85\u52a9\u51fd\u6570\u8fd8\u9700\u8981fs\u7b49\u4f9d\u8d56\u3002\u4f8b\u5b50\u4ee5\u5df2\u7ecf\u786e\u8ba4\u662fRNA\u57fa\u56e0\u8868\u8fbe\u8ba1\u6570\u768410x HDF5\u4e3a\u8f93\u5165\uff1b\u542bADT\u3001\u5176\u4ed6\u6a21\u6001\u6216\u4e0d\u540c\u7279\u5f81\u547d\u540d\u7684\u6587\u4ef6\u5e94\u5148\u6309\u6a21\u6001\u6838\u5bf9\uff0c\u4e0d\u80fd\u76f4\u63a5\u628a\u6240\u6709\u884c\u5f53\u4f5cRNA\u57fa\u56e0\u3002<\/p>\n

\u5148\u5efa\u7acb\u78c1\u76d8counts\u548cAssay5\u5bf9\u8c61<\/h2>\n

\u4f7f\u7528\u65b0\u7684\u5de5\u4f5c\u76ee\u5f55\uff0c\u4fdd\u7559\u539fHDF5\u4e0d\u52a8\u3002BPCells\u8d1f\u8d23\u78c1\u76d8\u77e9\u9635\u7684\u8bfb\u5199\uff0cSeurat\u4fdd\u5b58\u5bf9\u8c61\u7ed3\u6784\u548c\u8def\u5f84\u3002\u521b\u5efa\u4e4b\u540e\u6838\u5bf9assay\u7c7b\u3001\u7279\u5f81\u548c\u7ec6\u80de\u540d\uff0c\u4e0d\u8c03\u7528as.matrix\uff0c\u4e5f\u4e0d\u6839\u636e\u4e00\u4e2a\u5f88\u5c0f\u7684RDS\u5927\u5c0f\u5224\u65ad\u5b8c\u6574\u6570\u636e\u53ea\u5360\u5f88\u5c11\u7a7a\u95f4\u3002<\/p>\n

library(Seurat)\nlibrary(SeuratObject)\nlibrary(BPCells)\ndir.create("analysis_bundle", showWarnings=FALSE)\nbp_dir <- "analysis_bundle\/counts_bp"\nif (dir.exists(bp_dir)) stop("\u8bf7\u4f7f\u7528\u65b0\u7684\u8f93\u51fa\u76ee\u5f55\uff0c\u907f\u514d\u8986\u76d6\u5df2\u6709\u77e9\u9635")\nmat <- open_matrix_10x_hdf5("filtered_feature_bc_matrix.h5")\nwrite_matrix_dir(mat=mat, dir=bp_dir)\ncounts <- open_matrix_dir(bp_dir)\nobj <- CreateSeuratObject(counts=counts)\nstopifnot(inherits(obj[["RNA"]], "Assay5"),\n          identical(Layers(obj[["RNA"]]), "counts"))\nprint(list(dim=dim(obj[["RNA"]]), class=class(obj[["RNA"]]$counts)))\nwriteLines(capture.output(sessionInfo()), "analysis_bundle\/session.txt")<\/code><\/pre>\n
\u5efa\u7acbsketch\uff0c\u5e76\u53ea\u5728\u660e\u786e\u7684assay\u4e0a\u8ba1\u7b97<\/h2>\n
\u4e0b\u9762\u7684\u7ec6\u80de\u6570\u3001\u7ef4\u5ea6\u548c\u5206\u8fa8\u7387\u4ec5\u4e3a\u6f14\u793a\u53c2\u6570\uff0c\u8981\u7528\u76ee\u6807\u6570\u636e\u68c0\u9a8c\u3002\u793a\u4f8b\u5355counts\u5c42\u610f\u5473\u7740ncells\u5bf9\u5e94\u672c\u5c42\u62bd\u53d6\u91cf\uff1b\u591a\u5c42\u65f6\u5f53\u524d\u63a5\u53e3\u5141\u8bb8\u6309\u5c42\u6307\u5b9a\u6570\u91cf\uff0c\u5355\u4e2a\u6574\u6570\u4e5f\u53ef\u80fd\u6309\u6bcf\u5c42\u89e3\u91ca\uff0c\u4e0d\u80fd\u8bef\u4ee5\u4e3a\u603b\u6570\u6c38\u8fdc\u7b49\u4e8e\u8be5\u6574\u6570\u3002<\/p>\n
DefaultAssay(obj) <- "RNA"\nobj <- NormalizeData(obj)\nobj <- FindVariableFeatures(obj)\nobj <- SketchData(obj, assay="RNA", ncells=min(10000L, ncol(obj)),\n                  method="LeverageScore", sketched.assay="sketch", seed=2026L)\nDefaultAssay(obj) <- "sketch"\nobj <- FindVariableFeatures(obj)\nobj <- ScaleData(obj, features=VariableFeatures(obj))\nnpcs <- min(30L, length(VariableFeatures(obj))-1L, ncol(obj[["sketch"]])-1L)\nstopifnot(npcs>=2L, ncol(obj[["sketch"]])>50L)\nobj <- RunPCA(obj, npcs=npcs)\nobj <- FindNeighbors(obj, dims=seq_len(npcs))\nobj <- FindClusters(obj, resolution=0.5)\nobj <- RunUMAP(obj, dims=seq_len(npcs), return.model=TRUE)<\/code><\/pre>\n\n\n\n\n\n\n\n\n\n
\u5bf9\u8c61\u6216\u6b65\u9aa4<\/th>\n\u4e3b\u8981\u4f5c\u7528<\/th>\n\u5fc5\u987b\u6838\u5bf9\u7684\u8fb9\u754c<\/th>\n<\/tr>\n<\/thead>\n
RNA\u78c1\u76d8counts<\/td>\n\u4fdd\u7559\u5168\u90e8\u539f\u59cb\u8ba1\u6570\u8bbf\u95ee<\/td>\n\u540e\u7aef\u76ee\u5f55\u662f\u6570\u636e\u7684\u4e00\u90e8\u5206<\/td>\n<\/tr>\n
sketch assay<\/td>\n\u652f\u6301\u4e00\u90e8\u5206\u63a2\u7d22\u548c\u5efa\u6a21<\/td>\n\u4e0d\u662f\u5b8c\u6574\u6570\u636e\u7684\u540c\u4e49\u66ff\u8eab<\/td>\n<\/tr>\n
PCA\u4e0eUMAP\u6a21\u578b<\/td>\n\u5728\u62bd\u53d6\u7ec6\u80de\u4e0a\u5b66\u4e60\u8868\u793a<\/td>\n\u53c2\u6570\u4e0e\u7a00\u6709\u7fa4\u4f53\u8868\u73b0\u9700\u68c0\u67e5<\/td>\n<\/tr>\n
\u5168\u91cf\u6295\u5f71<\/td>\n\u6269\u5c55\u6240\u9009\u8868\u793a\u6216\u6807\u7b7e<\/td>\n\u4e0d\u7b49\u4e8e\u6240\u6709\u6b65\u9aa4\u5168\u91cf\u91cd\u7b97<\/td>\n<\/tr>\n
\u4fdd\u5b58\u4e0e\u8fc1\u79fb<\/td>\n\u4fdd\u7559\u5bf9\u8c61\u4e0e\u540e\u7aef\u4f9d\u8d56<\/td>\n\u4e0d\u80fd\u53ea\u590d\u5236\u4e00\u4e2aRDS\u6587\u4ef6<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
\u9700\u8981\u5168\u91cf\u6807\u7b7e\u65f6\uff0c\u518d\u660e\u786e\u6295\u5f71\u6b65\u9aa4<\/h2>\n
\u7528\u4e0esketch\u4e00\u81f4\u7684\u7ef4\u5ea6\u548cUMAP\u6a21\u578b\u6295\u5f71\uff0c\u5e76\u5206\u522b\u547d\u540d\u5168\u91cf\u7ed3\u679c\u3002\u5f97\u5230\u5168\u91cf\u6807\u7b7e\u540e\uff0c\u68c0\u67e5\u7ec6\u80de\u8986\u76d6\u548c\u5df2\u77e5\u6807\u8bb0\uff0c\u7279\u522b\u5173\u6ce8\u7a00\u6709\u7fa4\u4f53\u662f\u5426\u88ab\u8fc7\u5ea6\u5408\u5e76\u3002sketch\u6709\u81ea\u5df1\u7684\u62bd\u6837\u76ee\u6807\uff0c\u6807\u7b7e\u6295\u5f71\u4e5f\u6709\u8fd1\u4f3c\u6027\uff0c\u4e0d\u80fd\u51ed\u56fe\u5f62\u597d\u770b\u4fdd\u8bc1\u6bcf\u4e2a\u7a00\u6709\u7fa4\u4f53\u90fd\u88ab\u6b63\u786e\u53d1\u73b0\u3002<\/p>\n
obj <- ProjectData(obj, assay="RNA", sketched.assay="sketch",\n                   sketched.reduction="pca", full.reduction="pca.full",\n                   umap.model="umap", dims=seq_len(npcs),\n                   normalization.method="LogNormalize",\n                   refdata=list(cluster_full="seurat_clusters"))\nDefaultAssay(obj) <- "RNA"\nstopifnot(nrow(Embeddings(obj, "pca.full"))==ncol(obj[["RNA"]]))\nprint(table(is.na(obj$cluster_full)))\nSaveSeuratRds(obj, file="analysis_bundle\/analysis.rds",\n              move=FALSE, relative=TRUE)\ncheck <- LoadSeuratRds("analysis_bundle\/analysis.rds")\nprint(dim(check[["RNA"]]))<\/code><\/pre>\n
\u4fdd\u5b58\u3001\u8d44\u6e90\u548c\u4e0b\u4e00\u6b65\u9a8c\u6536<\/h2>\n
\u6b64\u5904\u540e\u7aef\u539f\u672c\u5efa\u5728bundle\u5185\uff0c\u4fdd\u5b58\u65f6\u663e\u5f0f\u4e0d\u79fb\u52a8\u5df2\u6709\u6570\u636e\uff0c\u5e76\u4f7f\u7528\u76f8\u5bf9\u8def\u5f84\u3002\u5c06\u5b8c\u6574\u76ee\u5f55\u590d\u5236\u5230\u65b0\u4f4d\u7f6e\u540e\uff0c\u8fd8\u5e94\u5728\u65b0R\u4f1a\u8bdd\u91cd\u65b0\u8f7d\u5165\u3001\u62bd\u67e5\u5c11\u91cf\u503c\u548c\u5fc5\u8981\u964d\u7ef4\u3002\u4e0d\u8981\u5728\u9a8c\u8bc1\u524d\u6e05\u7406\u539f\u59cb\u8f93\u5165\u6216\u540e\u7aef\u76ee\u5f55\uff1b\u5bf9\u8c61\u80fd\u88ab\u8bfb\u53d6\u4f46\u5916\u90e8\u8def\u5f84\u5931\u6548\uff0c\u540e\u7eed\u8bbf\u95ee\u4ecd\u4f1a\u5931\u8d25\u3002<\/p>\n
\u5c06\u6280\u672f\u9a8c\u8bc1\u4e0e\u7ec6\u80de\u8d28\u91cf\u5224\u65ad\u5206\u5f00<\/h2>\n
HDF5\u6587\u4ef6\u80fd\u591f\u88ab\u6253\u5f00\uff0c\u53ea\u8bf4\u660e\u8bfb\u53d6\u8def\u5f84\u53ef\u7528\u3002\u4ecd\u9700\u6309\u5b9e\u9a8c\u60c5\u51b5\u786e\u8ba4\u4f4e\u8d28\u91cf\u7ec6\u80de\u3001\u7a7a\u6db2\u6ef4\u53ca\u7279\u5f81\u547d\u540d\u7b49\u95ee\u9898\uff0c\u5e76\u4fdd\u5b58\u8d28\u91cf\u7b5b\u9009\u4f9d\u636e\u3002\u4e0d\u80fd\u4e3a\u4e86\u8ba9\u5bf9\u8c61\u66f4\u5c0f\u5c31\u968f\u610f\u5220\u6389\u96be\u5904\u7406\u7684\u6837\u672c\uff0c\u4e5f\u4e0d\u80fd\u628a\u6ca1\u6709\u505a\u8d28\u91cf\u68c0\u67e5\u7684\u793a\u4f8b\u6d41\u7a0b\u76f4\u63a5\u5f53\u4f5c\u6700\u7ec8\u79d1\u5b66\u7ed3\u679c\u3002<\/p>\n
\u5728\u5168\u91cf\u6295\u5f71\u524d\uff0c\u5148\u5728sketch\u4e2d\u67e5\u770b\u4e0e\u7814\u7a76\u95ee\u9898\u76f8\u5173\u7684\u6807\u8bb0\u548c\u6837\u672c\u8986\u76d6\u3002\u5982\u679c\u67d0\u4e2a\u5173\u952e\u7fa4\u4f53\u6839\u672c\u6ca1\u6709\u5408\u9002\u7684\u53c2\u8003\u7ec6\u80de\uff0c\u6295\u5f71\u4e0d\u4f1a\u81ea\u52a8\u63d0\u4f9b\u65b0\u7684\u8bc1\u636e\u3002\u5bf9\u9700\u8981\u6df1\u5165\u5206\u6790\u7684\u7fa4\u4f53\uff0c\u5e94\u8fd4\u56de\u539f\u59cb\u7ec6\u80de\u96c6\u5408\u5efa\u7acb\u9002\u7528\u7684\u540e\u7eed\u65b9\u6848\uff0c\u5e76\u8bf4\u660e\u8be5\u65b9\u6848\u7684\u8ba1\u7b97\u8303\u56f4\u3002<\/p>\n
\u5927\u89c4\u6a21\u7ed8\u56fe\u4e5f\u53ef\u80fd\u4ea7\u751f\u989d\u5916\u65f6\u95f4\u4e0e\u5185\u5b58\u9700\u6c42\u3002\u5148\u7528\u9002\u5f53\u8303\u56f4\u6838\u67e5\u8868\u8fbe\u548c\u6807\u7b7e\uff0c\u518d\u51b3\u5b9a\u662f\u5426\u8f93\u51fa\u5168\u91cf\u56fe\uff1b\u7ed8\u56fe\u6162\u3001\u540e\u7aef\u8def\u5f84\u5931\u6548\u548c\u6a21\u578b\u8ba1\u7b97\u4e0d\u8db3\uff0c\u5e94\u5206\u522b\u6392\u67e5\u3002\u6700\u7ec8\u4ea4\u63a5\u65f6\uff0c\u4fdd\u7559\u76ee\u5f55\u6e05\u5355\u3001\u7248\u672c\u4e0e\u5173\u952e\u68c0\u67e5\u7ed3\u679c\uff0c\u624d\u80fd\u8ba9\u65b0\u7684\u670d\u52a1\u5668\u9a8c\u8bc1\u540c\u4e00\u5957\u5bf9\u8c61\uff0c\u800c\u4e0d\u662f\u53ea\u6536\u5230\u4e00\u4e2a\u53ef\u4ee5\u6253\u5f00\u5916\u58f3\u7684RDS\u3002\u76ee\u6807\u8d26\u53f7\u8fd8\u5e94\u80fd\u8bfb\u53d6\u5168\u90e8\u540e\u7aef\u76ee\u5f55\uff0c\u6743\u9650\u9a8c\u6536\u4e5f\u5c5e\u4e8e\u4ea4\u63a5\u68c0\u67e5\u7684\u4e00\u90e8\u5206\u3002<\/p>\n
\u5c06\u6280\u672f\u9a8c\u8bc1\u4e0e\u7ec6\u80de\u8d28\u91cf\u5224\u65ad\u5206\u5f00<\/h2>\n
HDF5\u6587\u4ef6\u80fd\u591f\u88ab\u6253\u5f00\uff0c\u53ea\u8bf4\u660e\u8bfb\u53d6\u8def\u5f84\u53ef\u7528\u3002\u4ecd\u9700\u6309\u5b9e\u9a8c\u60c5\u51b5\u786e\u8ba4\u4f4e\u8d28\u91cf\u7ec6\u80de\u3001\u7a7a\u6db2\u6ef4\u53ca\u7279\u5f81\u547d\u540d\u7b49\u95ee\u9898\uff0c\u5e76\u4fdd\u5b58\u8d28\u91cf\u7b5b\u9009\u4f9d\u636e\u3002\u4e0d\u80fd\u4e3a\u4e86\u8ba9\u5bf9\u8c61\u66f4\u5c0f\u5c31\u968f\u610f\u5220\u6389\u96be\u5904\u7406\u7684\u6837\u672c\uff0c\u4e5f\u4e0d\u80fd\u628a\u6ca1\u6709\u505a\u8d28\u91cf\u68c0\u67e5\u7684\u793a\u4f8b\u6d41\u7a0b\u76f4\u63a5\u5f53\u4f5c\u6700\u7ec8\u79d1\u5b66\u7ed3\u679c\u3002<\/p>\n
\u5728\u5168\u91cf\u6295\u5f71\u524d\uff0c\u5148\u5728sketch\u4e2d\u67e5\u770b\u4e0e\u7814\u7a76\u95ee\u9898\u76f8\u5173\u7684\u6807\u8bb0\u548c\u6837\u672c\u8986\u76d6\u3002\u5982\u679c\u67d0\u4e2a\u5173\u952e\u7fa4\u4f53\u6839\u672c\u6ca1\u6709\u5408\u9002\u7684\u53c2\u8003\u7ec6\u80de\uff0c\u6295\u5f71\u4e0d\u4f1a\u81ea\u52a8\u63d0\u4f9b\u65b0\u7684\u8bc1\u636e\u3002\u5bf9\u9700\u8981\u6df1\u5165\u5206\u6790\u7684\u7fa4\u4f53\uff0c\u5e94\u8fd4\u56de\u539f\u59cb\u7ec6\u80de\u96c6\u5408\u5efa\u7acb\u9002\u7528\u7684\u540e\u7eed\u65b9\u6848\uff0c\u5e76\u8bf4\u660e\u8be5\u65b9\u6848\u7684\u8ba1\u7b97\u8303\u56f4\u3002<\/p>\n
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