{"id":26234,"date":"2024-01-25T12:12:04","date_gmt":"2024-01-25T04:12:04","guid":{"rendered":"http:\/\/www.biocloudservice.com\/wordpress\/?p=26234"},"modified":"2024-01-25T12:12:06","modified_gmt":"2024-01-25T04:12:06","slug":"%e5%8d%95%e7%bb%86%e8%83%9e%e6%b5%8b%e5%ba%8f%e5%88%86%e6%9e%90%ef%bc%88%e5%9b%9b%ef%bc%89r%e5%8c%85seurat%e4%b8%8b%e6%b8%b8%e5%88%86%e6%9e%90","status":"publish","type":"post","link":"http:\/\/www.biocloudservice.com\/wordpress\/?p=26234","title":{"rendered":"\u5355\u7ec6\u80de\u6d4b\u5e8f\u5206\u6790\uff08\u56db\uff09R\u5305Seurat\u4e0b\u6e38\u5206\u6790"},"content":{"rendered":"

<\/h1>\n

\u4e0a\u4e00\u671f\u5c0f\u679c\u7528loupe brosew\u8fdb\u4e00\u6b65\u63a2\u7d22\u5355\u7ec6\u80de\u6d4b\u5e8f\u5904\u7406\u7ed3\u679c\uff0c\u4f46\u662f\u5b83\u7684\u529f\u80fd\u6709\u9650\uff0c\u8fd8\u65e0\u6cd5\u5b9e\u73b0\u590d\u6742\u7684\u529f\u80fd\u3002\u5982\u679c\u8981\u505a\u66f4\u6df1\u5165\u7684\u5206\u6790\u662f\u8fd8\u4e0d\u591f\u7684\u3002\u6240\u4ee5\u4eca\u5929\u9686\u91cd\u5411\u5927\u5bb6\u4ecb\u7ecd\uff0cSeurat\u2014\u2014\u4e00\u4e2a\u4e13\u4e1a\u505a\u5355\u7ec6\u80de\u6d4b\u5e8f\u4e0b\u6e38\u5206\u6790\u7684R\u5305\u3002<\/p>\n

<\/p>\n

\u5728\u4e0a\u6e38\u5730\u5904\u7406\u4e2dCell Ranger\u751f\u6210\u4e86feature barcode\u77e9\u9635\uff0c\u5e76\u8fdb\u884c\u4e86\u57fa\u672c\u7684\u80cc\u666f\u8fc7\u6ee4\uff0c\u4f46\u662f\u8fd8\u8fdc\u8fdc\u4e0d\u591f\u3002\u5355\u7ec6\u80de\u6d4b\u5e8f\u66f4\u6df1\u5165\u7684\u6316\u6398\u53ef\u4ee5\u7528R\u5305Seurat\u3002<\/p>\n

Tools for Single Cell Genomics \u2022 Seurat (satijalab.org)<\/a><\/p>\n

\u5b83\u529f\u80fd\u5f3a\u5927\u53ef\u4ee5\u8fdb\u4e00\u6b65\u5730\u5b9e\u73b0\uff1a<\/p>\n

    \n
  1. \u8fdb\u4e00\u6b65\u8fc7\u6ee4<\/li>\n
  2. \u805a\u7c7b\uff0c\u5206\u7ec6\u80de\u4e9a\u7fa4<\/li>\n
  3. \u6807\u8bb0\u57fa\u56e0<\/li>\n
  4. \u53ef\u89c6\u5316\uff0c\u6bcf\u4e00\u6b65\u90fd\u53ef\u4ee5\u8fdb\u884c\u53ef\u89c6\u5316<\/li>\n
  5. \u65e0\u7f1d\u8bfb\u53d610\u00d7\u6570\u636e<\/li>\n
  6. ….<\/li>\n<\/ol>\n

    <\/p>\n

    \u8be5\u5305\u5728\u5355\u7ec6\u80de\u6d4b\u5e8f\u4e0b\u6e38\u5206\u6790\u9886\u57df\u975e\u5e38\u8457\u540d\u4e0e\u6743\u5a01\uff0c\u5176\u53d1\u5e03\u5730\u6bcf\u4e2a\u7248\u672c\u90fd\u6709\u9ad8\u6c34\u5e73\u6587\u7ae0\u53d1\u5e03\u3002<\/p>\n

    \u4e0b\u9762\u6211\u4eec\u901a\u8fc7\u4e00\u4e2a\u6848\u4f8b\u6765\u5f00\u59cb\u5b66\u4e60\u5427~<\/p>\n

    \u5b89\u88c5\u4e0e\u52a0\u8f7d<\/h2>\n

    install packages(“Seurat”)<\/p>\n

    library<\/a>(Seurat<\/a>)<\/p>\n

    library(dplyr)<\/p>\n

    library(patchwork)<\/p>\n

    \u52a0\u8f7d\u6848\u4f8b\u6570\u636e<\/h2>\n

    \u5728\u672c\u6559\u7a0b\u4e2d\uff0c\u6211\u4eec\u5c06\u5206\u679010X Genomics\u514d\u8d39\u63d0\u4f9b\u7684\u5916\u5468\u8840\u5355\u6838\u7ec6\u80de\uff08PBMC\uff09\u6570\u636e\u96c6\u3002\u67092700\u4e2a\u5355\u7ec6\u80de\u5728Illumina NextSeq 500\u4e0a\u8fdb\u884c\u4e86\u6d4b\u5e8f\u3002<\/p>\n

    https:\/\/cf.10xgenomics.com\/samples\/cell\/pbmc3k\/pbmc3k_filtered_gene_bc_matrices.tar.gz<\/a><\/p>\n

    \u539f\u59cb\u6570\u636e\u4e0b\u8f7d\u94fe\u63a5\u3002<\/p>\n

    pbmc.data <- Read10X(data.dir = “pbmc3k\/filtered_gene_bc_matrices\/hg19\/”)<\/p>\n

    \u4f7f\u7528Read10X\u51fd\u6570\u8bfb\u53d610\u00d7genomics \u5e73\u53f0cellranger pipline\u7684\u8f93\u51fa\uff0c\u8fd4\u56de\u552f\u4e00\u7684\u8ba1\u6570\u77e9\u9635\u3002\u8be5\u77e9\u9635\u4e2d\u7684\u503c\u8868\u793a\u5728\u6bcf\u4e2a\u7ec6\u80de\uff08\u5217\uff09\u4e2d\u68c0\u6d4b\u5230\u7684\u6bcf\u4e2a\u7279\u5f81\uff08\u5373\u57fa\u56e0\uff0c\u884c\uff09\u7684\u5206\u5b50\u6570\u91cf\u3002<\/p>\n

    \u751f\u6210Seurat\u5bf9\u8c61<\/h2>\n

    pbmc <- CreateSeuratObject(counts = pbmc.data, project = “pbmc3k”, min.cells = 3, min.features = 200)<\/p>\n

    \u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u4f7f\u7528CreateSeuratObject\u6765\u521b\u5efaSeurat\u5bf9\u8c61\u3002\u8be5\u5bf9\u8c61\u5145\u5f53\u4e00\u4e2a\u5bb9\u5668\uff0c\u5176\u4e2d\u5305\u542b\u5355\u7ec6\u80de\u6570\u636e\u96c6\u7684\u6570\u636e\uff08\u5982\u8ba1\u6570\u77e9\u9635\uff09\u548c\u5206\u6790\uff08\u5982PCA\u6216\u805a\u7c7b\u7ed3\u679c\uff09\u3002<\/p>\n

    min.cells = 3\uff0c\u662f\u6307\u6bcf\u4e2a\u7ec6\u80de\u4e2dUMIs\u7684\u4e2a\u6570\u6700\u5c0f\u662f3<\/p>\n

    min.features = 200\uff0c\u662f\u6307\u6bcf\u4e2a\u7ec6\u80de\u4e2d\u57fa\u56e0\u6570\u76ee\u6700\u5c11\u4e3a200\uff0c\u5426\u5219\u4f1a\u88ab\u8fc7\u6ee4\u6389\u3002<\/p>\n

    <\/p>\n

    \u67e5\u770b\u6570\u636e\u96c6\u7ef4\u5ea6\uff0c\u670932738\u4e2a\u57fa\u56e0\uff0c2700\u4e2a\u7ec6\u80de\u3002<\/p>\n

    \u6570\u636e\u8d28\u63a7\u4e0e\u8fc7\u6ee4<\/h2>\n

    \u5bf9\u4e8e\u73b0\u5728\u7684\u6570\u636e\u6211\u4eec\u4ecd\u7136\u9700\u8981\u8fdb\u4e00\u6b65\u7684\u8fc7\u6ee4\u3002\u6765\u53bb\u9664\u7a7a\u7ec6\u80de\uff0c\u4e0e\u6b7b\u7ec6\u80de\u3002<\/p>\n

    \u90a3\u4e48\u6211\u4eec\u8be5\u5982\u4f55\u5224\u65ad\u4e00\u4e2a\u7ec6\u80de\u662f\u6b7b\u7ec6\u80de\u8fd8\u662f\u7a7a\u7ec6\u80de\u5462\uff1f\u6211\u4eec\u6709\u5bf9\u5e94\u4e4b\u7b56\uff0c\u5982\u679c\u662f\u7a7a\u7ec6\u80de\u7684\u753b\u90a3\u4e48\u6355\u83b7\u5230\u7684umi\u6570\u91cf\u5c31\u4f1a\u5f88\u5c11\u3002\u5982\u679c\u662f\u6b7b\u7ec6\u80de\u5462\uff0c\u7ebf\u7c92\u4f53\u57fa\u56e0\u7684\u6bd4\u4f8b\u5c31\u4f1a\u5f88\u9ad8\uff0c\u6211\u4eec\u5c06\u6bd4\u4f8b\u8fc7\u9ad8\u7684\u7ec6\u80de\u8fc7\u6ee4\u6389\u5373\u53ef\u3002<\/p>\n

    \u6211\u4eec\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\uff0c\u521b\u5efa\u4e00\u4e2a\u7ebf\u7c92\u4f53\u57fa\u56e0\u5217\u8868\u3002<\/p>\n

    pbmc[[‘percent.mt’]] <- PercentageFeatureSet(pbmc,pattern = “^MT-“)<\/p>\n

    pattern = “^MT-“\u7ebf\u7c92\u4f53\u57fa\u56e0\u4f1a\u6709\u6807\u6ce8MT\u8fd9\u91cc\u6211\u4eec\u8bbe\u7f6ePatterns\u4e3aMT\u5373\u53ef\u3002<\/p>\n

    VlnPlot(pbmc,features = c(“nFeature_RNA”,”nCount_RNA”,”percent.mt”),ncol=3)<\/p>\n

    \u9009\u62e9\u4e09\u4e2a\u6307\u6807”nFeature_RNA”,”nCount_RNA”,”percent.mt”\u7ed8\u5236\u6570\u636e\u7684\u5c0f\u63d0\u7434\u56fe\uff0c<\/p>\n

    <\/p>\n

    \u56fe\u4e2d\u7684\u6bcf\u4e2a\u70b9\u5373\u4e3a\u4e00\u4e2a\u5355\u7ec6\u80de\uff0c\u53ef\u4ee5\u770b\u5230\u6709\u96f6\u661f\u51e0\u4e2a\u7ec6\u80de\u5904\u5728\u56fe\u7684\u4e0a\u65b9\uff0c\u8fd9\u4e9b\u70b9\u4f1a\u5f71\u54cd\u5206\u6790\u7684\u7ed3\u679c\uff0c\u6211\u4eec\u5c06\u5176\u8fc7\u6ee4\u6389\u3002<\/p>\n

    \u8fc7\u6ee4\u6761\u4ef6\u6839\u636e\u4e0d\u540c\u6d4b\u5e8f\u9879\u76ee\u8fdb\u884c\u8c03\u6574<\/p>\n

    pbmc <- subset(pbmc, subset = nFeature_RNA > 200 & nFeature_RNA < 2500 & percent.mt < 5)<\/p>\n

    \u8fd9\u91cc\u6211\u4eec\u8fc7\u6ee4 feature counts> 2,500 or < 200\uff0c>5% mitochondrial counts<\/p>\n

    <\/p>\n

    \u8fc7\u6ee4\u540e\u57fa\u56e0\u6570\u76ee\u4e0b\u964d\u81f313714\u4e2a\uff0c\u7ec6\u80de\u6570\u76ee\u4e0b\u964d\u81f32638<\/p>\n

    plot1 <- FeatureScatter(pbmc,feature1 = “nCount_RNA”,feature2 = “percent.mt”)<\/p>\n

    plot2 <- FeatureScatter(pbmc,feature1 = “nCount_RNA”,feature2 = “nFeature_RNA”)<\/p>\n

    plot1+plot2<\/p>\n

    <\/p>\n

    \u8fc7\u6ee4\u540e\u7ebf\u7c92\u4f53\u57fa\u56e0\u90fd\u5904\u57285%\u4ee5\u4e0b\uff0c\u5355\u7ec6\u80de\u7684\u6570\u636e\u968f\u7740umi counts\u6570\u76ee\u589e\u591a\uff0c\u57fa\u56e0\u6570\u76ee\u4e5f\u968f\u4e4b\u589e\u591a\uff0c\u5448\u73b0\u7ebf\u6027\u5173\u7cfb\u3002<\/p>\n

    \u6807\u51c6\u5316\u6570\u636e<\/h2>\n

    \u7531\u4e8e\u6bcf\u4e2a\u7ec6\u80de\u6d4b\u5e8f\u6df1\u5ea6\u4e0d\u540c\uff08\u6709\u7684\u7ec6\u80de\u6d4b\u7684counts\u6570\u76ee\u591a\uff0c\u57fa\u56e0\u591a\uff0c\u800c\u6709\u7684\u7ec6\u80decounts\u5c11\u57fa\u56e0\u5c11\uff09\u6211\u4eec\u9700\u8981\u5bf9\u5176\u8fdb\u884c\u6807\u51c6\u5316\uff0c\u624d\u80fd\u8fdb\u884c\u8fdb\u4e00\u6b65\u7684\u5dee\u5f02\u8868\u8fbe\u8ba1\u7b97\u3002<\/p>\n

    pbmc <- NormalizeData(pbmc, normalization.method = “LogNormalize”, scale.factor = 10000)<\/p>\n

    \u8fd9\u91cc\u6211\u4eec\u9009\u62e9\u5e38\u7528\u7684LogNormalize\u7b97\u6cd5\u3002scale.factor\u9009\u62e9\u9ed8\u8ba4\u3002<\/p>\n

    \u8bc6\u522b\u5dee\u5f02\u8868\u8fbe\u57fa\u56e0<\/h2>\n

    #\u9ed8\u8ba42000\u4e2a\uff0c\u53ef\u4ee5\u901a\u8fc7nfeatures\u8c03\u6574<\/p>\n

    pbmc <- FindVariableFeatures(pbmc, selection.method = “vst”, nfeatures = 2000)<\/p>\n

    \u63a5\u4e0b\u6765\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528FindVariableFeatures\u51fd\u6570\u6765\u8fdb\u884c\u5dee\u5f02\u57fa\u56e0\u8bc6\u522b\u3002<\/p>\n

    top10 <- head(VariableFeatures(pbmc), 10)<\/p>\n

    \u524d10\u57fa\u56e0<\/p>\n

    <\/p>\n

    \u53ef\u89c6\u5316\u524d10\u57fa\u56e0<\/p>\n

    plot1 <- VariableFeaturePlot(pbmc)<\/p>\n

    plot1<\/p>\n

    plot2 <- LabelPoints(plot = plot1,points = top10)<\/p>\n

    plot2<\/p>\n

    plot1+plot2<\/p>\n

    <\/p>\n

    \u9884\u77e5\u540e\u7eed\u7684\u5206\u6790\u5982\u4f55\uff0c\u8bf7\u5173\u6ce8\u672c\u516c\u4f17\u53f7\uff0c\u5c0f\u679c\u5e26\u4f60\u9886\u7565\u751f\u4fe1\u5206\u6790\u7684\u9b45\u529b\u3002<\/p>\n

    \u5355\u7ec6\u80de\u6d4b\u5e8f\u5206\u6790\u5185\u5bb9\u6b22\u8fce\u5c1d\u8bd5\u672c\u516c\u53f8\u65b0\u5f00\u53d1\u7684\u4e91\u5e73\u53f0\u751f\u7269\u4fe1\u606f\u5206\u6790\u5c0f\u5de5\u5177\uff0c\u96f6\u4ee3\u7801\u5b8c\u6210\u5206\u6790\uff0c\u4e91\u5e73\u53f0\u7f51\u5740\uff1ahttp:\/\/www.biocloudservice.com\/home.html\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"

    \u4e0a\u4e00\u671f\u5c0f\u679c\u7528loupe brosew\u8fdb\u4e00\u6b65\u63a2\u7d22\u5355\u7ec6\u80de\u6d4b\u5e8f\u5904\u7406\u7ed3\u679c\uff0c\u4f46\u662f\u5b83\u7684\u529f\u80fd\u6709\u9650\uff0c\u8fd8\u65e0\u6cd5\u5b9e\u73b0\u590d\u6742\u7684\u529f\u80fd\u3002\u5982\u679c […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":""},"categories":[1],"tags":[],"jetpack_featured_media_url":"","_links":{"self":[{"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/26234"}],"collection":[{"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=26234"}],"version-history":[{"count":1,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/26234\/revisions"}],"predecessor-version":[{"id":26243,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/26234\/revisions\/26243"}],"wp:attachment":[{"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=26234"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=26234"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=26234"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}