{"id":29395,"date":"2024-02-22T17:54:42","date_gmt":"2024-02-22T09:54:42","guid":{"rendered":"http:\/\/www.biocloudservice.com\/wordpress\/?p=29395"},"modified":"2024-02-22T17:54:44","modified_gmt":"2024-02-22T09:54:44","slug":"%e5%8d%95%e7%bb%86%e8%83%9e%e5%86%85%e7%bd%ae%e6%95%b0%e6%8d%ae%e5%a4%84%e7%90%86%e5%92%8c%e5%88%86%e6%9e%90","status":"publish","type":"post","link":"http:\/\/www.biocloudservice.com\/wordpress\/?p=29395","title":{"rendered":"\u5355\u7ec6\u80de\u5185\u7f6e\u6570\u636e\u5904\u7406\u548c\u5206\u6790"},"content":{"rendered":"

\n \u5355\u7ec6\u80de\u5185\u7f6e\u6570\u636e\u5904\u7406\u548c\u5206\u6790\n<\/p>\n

\n \u4eca\u5929\u5c0f\u679c\u60f3\u5b66\u4e60\u5206\u4eab\u4e00\u4e0b\u5355\u7ec6\u80de\u5185\u7f6e\u6570\u636e\u7684\u5904\u7406\u548c\u5206\u6790\u8fc7\u7a0b\uff0c\u63d0\u9ad8\u5927\u5bb6\u5bf9\u516c\u5171\u6570\u636e\u7684\u5229\u7528\u6548\u7387\uff0c\u6709\u9700\u8981\u7684\u53ef\u4ee5\u5b66\u4e60\u638c\u63e1\u4e00\u4e0b\u5965\uff0c\u4ee3\u7801\u5982\u4e0b\uff1a\n<\/p>

  1. \n \u5b89\u88c5\u9700\u8981\u7684R\u5305\n<\/li><\/ol>\n

    \n install.packages(\u201cBiocManager\u201d)\n<\/p>\n

    \n BiocManager::install(\u201cSeurat\u201d)\n<\/p>\n

    \n devtools::install_github(‘satijalab\/seurat-data’,force = TRUE)\n<\/p>\n

    \n install.packages(\u201cpatchwork\u201d)\n<\/p>

    1. \n \u5bfc\u5165\u9700\u8981\u7684R\u5305\n<\/li><\/ol>\n

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

      \n library(SeuratData)\n<\/p>\n

      \n Library(patchwork)\n<\/p>

      1. \n \u4ee3\u7801\u5c55\u793a\n<\/li><\/ol>\n

        \n InstallData(“ifnb”)\n<\/p>\n

        \n LoadData(“ifnb”)\n<\/p>\n

        \n # ifnb\u6570\u636e\u96c6\u4e2d\u5305\u542b\u4e24\u4e2a\u6837\u672c\u6570\u636e\uff0c\u5206\u522b\u4e3aCTRL\u548cSTIM\n<\/p>\n

        \n head(ifnb@meta.data)\n<\/p>\n

        \n table(ifnb@meta.data$stim)\n<\/p>\n

        \n # \u6570\u636e\u62c6\u5206\u6210\u4e24\u7ec4(STIM\u548cCTRL)\n<\/p>\n

        \n # \u4f7f\u7528splitobject\u5c06ifnb\u6570\u636e\u96c6\u5206\u5272\u6210\u4e24\u4e2aseurat\u5bf9\u8c61\u7684\u5217\u8868(STIM\u548cCTRL)\n<\/p>\n

        \n ifnb.list <- SplitObject(ifnb, split.by = “stim”)\n<\/p>\n

        \n # \u5bf9\u4e24\u4e2a\u6570\u636e\u96c6\u5355\u72ec\u8fdb\u884cnormalize\u5e76\u8bc6\u522b\u5404\u81ea\u7684\u9ad8\u53d8\u5f02\u57fa\u56e0\n<\/p>\n

        \n ifnb.list <- lapply(X = ifnb.list, FUN = function(x) {\n<\/p>\n

        \n x <- NormalizeData(x)\n<\/p>\n

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

        \n })\n<\/p>\n

        \n # \u8ba1\u7b97\u4e24\u4e2a\u6570\u636e\u4e2d\u6392\u5b8crank\u540etop2000\u7684\u9ad8\u53d8\u5f02\u57fa\u56e0\n<\/p>\n

        \n features <- SelectIntegrationFeatures(object.list = ifnb.list, nfeatures = 2000)\n<\/p>\n

        \n # \u4f7f\u7528\u4e0a\u8ff0\u9ad8\u53d8\u5f02\u57fa\u56e0\u5728\u4e24\u4e2a\u57fa\u56e0\u96c6\u4e2d\u5206\u522b\u6267\u884cPCA\n<\/p>\n

        \n ifnb.list <- lapply(X = ifnb.list, FUN = function(x) {\n<\/p>\n

        \n x <- ScaleData(x, features = features, verbose = T)\n<\/p>\n

        \n x <- RunPCA(x, features = features, verbose = T)\n<\/p>\n

        \n })\n<\/p>\n

        \n ## \u5bf9\u4e24\u4e2a\u6570\u636e\u96c6\u8fdb\u884c\u6574\u5408\n<\/p>\n

        \n # \u9996\u5148\u4f7f\u7528findinintegrationanchors\u51fd\u6570\u6807\u8bc6\u951a\u70b9\uff0c\u7136\u540e\u4f7f\u7528IntegrateData\u51fd\u6570\u5c06\u4e24\u6570\u636e\u96c6\u6574\u5408\u5728\u4e00\u8d77\n<\/p>\n

        \n # \u53ef\u4ee5\u901a\u8fc7\u8c03\u6574k.anchor\u53c2\u6570\u8c03\u6574\u4e24\u4e2a\u6837\u672c\u6574\u5408\u7684\u5f3a\u5ea6\uff0c\u9ed8\u8ba4\u4e3a5\uff0c\u6570\u5b57\u8d8a\u5927\u6574\u5408\u5f3a\u5ea6\u8d8a\u5f3a\n<\/p>\n

        \n immune.anchors <- FindIntegrationAnchors(object.list = ifnb.list, anchor.features = features, reduction = “rpca”, k.anchor = 20)\n<\/p>\n

        \n immune<- IntegrateData(anchorset = immune.anchors)\n<\/p>\n

        \n # \u5e38\u89c4\u6d41\u7a0b\uff0cscale\u6570\u636e\uff0c\u8dd1PCA\uff0c\u4f7f\u7528\u524d30\u4e2aPC\u8fdb\u884c\u964d\u7ef4\u8dd1UMAP\uff0c\u8ba1\u7b97Neighbors\uff0c\u5206cluster\n<\/p>\n

        \n immune <- ScaleData(immune, verbose = FALSE)\n<\/p>\n

        \n immune <- RunPCA(immune, npcs = 30, verbose = FALSE)\n<\/p>\n

        \n immune <- RunUMAP(immune, reduction = “pca”, dims = 1:30)\n<\/p>\n

        \n immune <- FindNeighbors(immune, reduction = “pca”, dims = 1:30)\n<\/p>\n

        \n immune<- FindClusters(immune, resolution = 0.5)\n<\/p>\n

        \n immune@meta.data\n<\/p>\n

        \n \"Dingtalk_20230308171341\"\n<\/p>\n

        \n # \u53ef\u89c6\u5316\n<\/p>\n

        \n p <- DimPlot(immune, reduction = “umap”, group.by = “stim”)\n<\/p>\n

        \n p21<- DimPlot(immune, reduction = “umap”, group.by = “seurat_annotations”,label = TRUE,repel = TRUE)\n<\/p>\n

        \n #\u62fc\u56fe\n<\/p>\n

        \n pdf(“immune.UMAP.pdf”, height = 5,width = 12)\n<\/p>\n

        \n p+ p1\n<\/p>\n

        \n dev.off()\n<\/p>\n

        \n \"Dingtalk_20230308171013\"\n<\/p>\n

        \n \u6700\u7ec8\u6211\u4eec\u5bf9\u5185\u7f6e\u6570\u636e\u96c6ifnb\u8fdb\u884c\u4e86\u6570\u636e\u5904\u7406\uff0c\u5176\u4e2d\u5904\u7406\u8fc7\u7a0b\u5305\u542b\u4e86\u6570\u636e\u96c6\u7684\u6574\u5408\u548c\u62c6\u5206\u7b49\u8fc7\u7a0b\uff0c\u5e76\u8fdb\u884c\u4e86\u5355\u7ec6\u80de\u5e38\u89c4\u6d41\u7a0b\u5206\u6790\uff0c\u8be5\u5206\u6790\u6240\u9700\u8981\u7684R\u5305\u672c\u516c\u53f8\u670d\u52a1\u5668\u5df2\u7ecf\u5168\u90e8\u5b89\u88c5\uff0c\u6709\u9700\u8981\u7684\u5c0f\u4f19\u4f34\u53ef\u4ee5\u8054\u7cfb\u5c0f\u679c\u5965\uff0c\u4eca\u5929\u5c0f\u679c\u7684\u5206\u4eab\u5c31\u5230\u8fd9\u91cc\u3002\n<\/p>\n\n\n

        \u4eca\u5929\u5c0f\u679c\u60f3\u5b66\u4e60\u5206\u4eab\u4e00\u4e0b\u5355\u7ec6\u80de\u5185\u7f6e\u6570\u636e\u7684\u5904\u7406\u548c\u5206\u6790\u8fc7\u7a0b\uff0c\u63d0\u9ad8\u5927\u5bb6\u5bf9\u516c\u5171\u6570\u636e\u7684\u5229\u7528\u6548\u7387\uff0c\u6709\u9700\u8981\u7684\u53ef\u4ee5\u5b66\u4e60\u638c\u63e1\u4e00\u4e0b\u5965\uff0c\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n\n\n\n

          \n
        1. \u5b89\u88c5\u9700\u8981\u7684R\u5305<\/li>\n<\/ol>\n\n\n\n

          install.packages(\u201cBiocManager\u201d)<\/p>\n\n\n\n

          BiocManager::install(\u201cSeurat\u201d)<\/p>\n\n\n\n

          devtools::install_github(‘satijalab\/seurat-data’,force = TRUE)<\/p>\n\n\n\n

          install.packages(\u201cpatchwork\u201d)<\/p>\n\n\n\n

            \n
          1. \u5bfc\u5165\u9700\u8981\u7684R\u5305<\/li>\n<\/ol>\n\n\n\n

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

            library(SeuratData)<\/p>\n\n\n\n

            Library(patchwork)<\/p>\n\n\n\n

              \n
            1. \u4ee3\u7801\u5c55\u793a<\/li>\n<\/ol>\n\n\n\n

              InstallData(“ifnb”)<\/p>\n\n\n\n

              LoadData(“ifnb”)<\/p>\n\n\n\n

              # ifnb\u6570\u636e\u96c6\u4e2d\u5305\u542b\u4e24\u4e2a\u6837\u672c\u6570\u636e\uff0c\u5206\u522b\u4e3aCTRL\u548cSTIM<\/p>\n\n\n\n

              head(ifnb@meta.data)<\/p>\n\n\n\n

              table(ifnb@meta.data$stim)<\/p>\n\n\n\n

              # \u6570\u636e\u62c6\u5206\u6210\u4e24\u7ec4(STIM\u548cCTRL)<\/p>\n\n\n\n

              # \u4f7f\u7528splitobject\u5c06ifnb\u6570\u636e\u96c6\u5206\u5272\u6210\u4e24\u4e2aseurat\u5bf9\u8c61\u7684\u5217\u8868(STIM\u548cCTRL)<\/p>\n\n\n\n

              ifnb.list <- SplitObject(ifnb, split.by = “stim”)<\/p>\n\n\n\n

              # \u5bf9\u4e24\u4e2a\u6570\u636e\u96c6\u5355\u72ec\u8fdb\u884cnormalize\u5e76\u8bc6\u522b\u5404\u81ea\u7684\u9ad8\u53d8\u5f02\u57fa\u56e0<\/p>\n\n\n\n

              ifnb.list <- lapply(X = ifnb.list, FUN = function(x) {<\/p>\n\n\n\n

              x <- NormalizeData(x)<\/p>\n\n\n\n

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

              })<\/p>\n\n\n\n

              # \u8ba1\u7b97\u4e24\u4e2a\u6570\u636e\u4e2d\u6392\u5b8crank\u540etop2000\u7684\u9ad8\u53d8\u5f02\u57fa\u56e0<\/p>\n\n\n\n

              features <- SelectIntegrationFeatures(object.list = ifnb.list, nfeatures = 2000)<\/p>\n\n\n\n

              # \u4f7f\u7528\u4e0a\u8ff0\u9ad8\u53d8\u5f02\u57fa\u56e0\u5728\u4e24\u4e2a\u57fa\u56e0\u96c6\u4e2d\u5206\u522b\u6267\u884cPCA<\/p>\n\n\n\n

              ifnb.list <- lapply(X = ifnb.list, FUN = function(x) {<\/p>\n\n\n\n

              x <- ScaleData(x, features = features, verbose = T)<\/p>\n\n\n\n

              x <- RunPCA(x, features = features, verbose = T)<\/p>\n\n\n\n

              })<\/p>\n\n\n\n

              ## \u5bf9\u4e24\u4e2a\u6570\u636e\u96c6\u8fdb\u884c\u6574\u5408<\/p>\n\n\n\n

              # \u9996\u5148\u4f7f\u7528findinintegrationanchors\u51fd\u6570\u6807\u8bc6\u951a\u70b9\uff0c\u7136\u540e\u4f7f\u7528IntegrateData\u51fd\u6570\u5c06\u4e24\u6570\u636e\u96c6\u6574\u5408\u5728\u4e00\u8d77<\/p>\n\n\n\n

              # \u53ef\u4ee5\u901a\u8fc7\u8c03\u6574k.anchor\u53c2\u6570\u8c03\u6574\u4e24\u4e2a\u6837\u672c\u6574\u5408\u7684\u5f3a\u5ea6\uff0c\u9ed8\u8ba4\u4e3a5\uff0c\u6570\u5b57\u8d8a\u5927\u6574\u5408\u5f3a\u5ea6\u8d8a\u5f3a<\/p>\n\n\n\n

              immune.anchors <- FindIntegrationAnchors(object.list = ifnb.list, anchor.features = features, reduction = “rpca”, k.anchor = 20)<\/p>\n\n\n\n

              immune<- IntegrateData(anchorset = immune.anchors)<\/p>\n\n\n\n

              # \u5e38\u89c4\u6d41\u7a0b\uff0cscale\u6570\u636e\uff0c\u8dd1PCA\uff0c\u4f7f\u7528\u524d30\u4e2aPC\u8fdb\u884c\u964d\u7ef4\u8dd1UMAP\uff0c\u8ba1\u7b97Neighbors\uff0c\u5206cluster<\/p>\n\n\n\n

              immune <- ScaleData(immune, verbose = FALSE)<\/p>\n\n\n\n

              immune <- RunPCA(immune, npcs = 30, verbose = FALSE)<\/p>\n\n\n\n

              immune <- RunUMAP(immune, reduction = “pca”, dims = 1:30)<\/p>\n\n\n\n

              immune <- FindNeighbors(immune, reduction = “pca”, dims = 1:30)<\/p>\n\n\n\n

              immune<- FindClusters(immune, resolution = 0.5)<\/p>\n\n\n\n

              immune@meta.data<\/p>\n\n\n\n

              \"\"<\/figure>\n\n\n\n

              # \u53ef\u89c6\u5316<\/p>\n\n\n\n

              p <- DimPlot(immune, reduction = “umap”, group.by = “stim”)<\/p>\n\n\n\n

              p21<- DimPlot(immune, reduction = “umap”, group.by = “seurat_annotations”,label = TRUE,repel = TRUE)<\/p>\n\n\n\n

              #\u62fc\u56fe<\/p>\n\n\n\n

              pdf(“immune.UMAP.pdf”, height = 5,width = 12)<\/p>\n\n\n\n

              p+ p1<\/p>\n\n\n\n

              dev.off()<\/p>\n\n\n\n

              \"\"<\/figure>\n\n\n\n

              \u6700\u7ec8\u6211\u4eec\u5bf9\u5185\u7f6e\u6570\u636e\u96c6ifnb\u8fdb\u884c\u4e86\u6570\u636e\u5904\u7406\uff0c\u5176\u4e2d\u5904\u7406\u8fc7\u7a0b\u5305\u542b\u4e86\u6570\u636e\u96c6\u7684\u6574\u5408\u548c\u62c6\u5206\u7b49\u8fc7\u7a0b\uff0c\u5e76\u8fdb\u884c\u4e86\u5355\u7ec6\u80de\u5e38\u89c4\u6d41\u7a0b\u5206\u6790\uff0c\u8be5\u5206\u6790\u6240\u9700\u8981\u7684R\u5305\u672c\u516c\u53f8\u670d\u52a1\u5668\u5df2\u7ecf\u5168\u90e8\u5b89\u88c5\uff0c\u6709\u9700\u8981\u7684\u5c0f\u4f19\u4f34\u53ef\u4ee5\u8054\u7cfb\u5c0f\u679c\u5965\uff0c\u4eca\u5929\u5c0f\u679c\u7684\u5206\u4eab\u5c31\u5230\u8fd9\u91cc\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"

              \u5355\u7ec6\u80de\u5185\u7f6e\u6570\u636e\u5904\u7406\u548c\u5206\u6790 \u4eca\u5929\u5c0f\u679c\u60f3\u5b66\u4e60\u5206\u4eab\u4e00\u4e0b\u5355\u7ec6\u80de\u5185\u7f6e\u6570\u636e\u7684\u5904\u7406\u548c\u5206\u6790\u8fc7\u7a0b\uff0c\u63d0\u9ad8\u5927\u5bb6\u5bf9\u516c\u5171\u6570\u636e\u7684\u5229\u7528\u6548\u7387\uff0c […]<\/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\/29395"}],"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=29395"}],"version-history":[{"count":1,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/29395\/revisions"}],"predecessor-version":[{"id":29402,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/29395\/revisions\/29402"}],"wp:attachment":[{"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=29395"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=29395"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=29395"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}