{"id":16101,"date":"2023-10-20T15:58:35","date_gmt":"2023-10-20T07:58:35","guid":{"rendered":"http:\/\/www.biocloudservice.com\/wordpress\/?p=16101"},"modified":"2023-10-20T15:58:37","modified_gmt":"2023-10-20T07:58:37","slug":"%e3%80%90dropclust%e3%80%91%e6%89%8b%e6%8a%8a%e6%89%8b%e6%95%99%e4%bd%a0%e8%bf%9b%e8%a1%8c%e5%85%a8%e5%9f%ba%e5%9b%a0%e7%bb%84%e5%b0%ba%e5%ba%a6%e9%89%b4%e5%ae%9a%e5%b9%b6%e5%8f%af%e8%a7%86%e5%8c%96","status":"publish","type":"post","link":"http:\/\/www.biocloudservice.com\/wordpress\/?p=16101","title":{"rendered":"\u3010dropClust\u3011\u624b\u628a\u624b\u6559\u4f60\u8fdb\u884c\u5168\u57fa\u56e0\u7ec4\u5c3a\u5ea6\u9274\u5b9a\u5e76\u53ef\u89c6\u5316\u7fa4\u4f53\u9057\u4f20\u7ed3\u6784"},"content":{"rendered":"<p>\u4eca\u5929\u5c0f\u82b1\u7ed9\u5927\u5bb6\u4ecb\u7ecd\u4e00\u4e2a\u7b80\u5355\u597d\u7528\u7684\u751f\u4fe1\u5206\u6790\u5de5\u5177\u7bb1\u2014\u2014<strong>dropClust<\/strong> \u662f\u4e00\u4e2a\u7528\u4e8e\u5728\u5168\u57fa\u56e0\u7ec4\u5c3a\u5ea6\u9274\u5b9a\u5e76\u53ef\u89c6\u5316\u7fa4\u4f53\u9057\u4f20\u7ed3\u6784\u7684R\u5305\u3002<\/p>\n<p><img decoding=\"async\" loading=\"lazy\" width=\"640\" height=\"200\" class=\"wp-image-16102\" src=\"https:\/\/i0.wp.com\/www.biocloudservice.com\/wordpress\/wp-content\/uploads\/2023\/10\/word-image-16101-1.png?resize=640%2C200\" srcset=\"https:\/\/i0.wp.com\/www.biocloudservice.com\/wordpress\/wp-content\/uploads\/2023\/10\/word-image-16101-1.png?w=1233 1233w, https:\/\/i0.wp.com\/www.biocloudservice.com\/wordpress\/wp-content\/uploads\/2023\/10\/word-image-16101-1.png?resize=300%2C94 300w, https:\/\/i0.wp.com\/www.biocloudservice.com\/wordpress\/wp-content\/uploads\/2023\/10\/word-image-16101-1.png?resize=1024%2C320 1024w, https:\/\/i0.wp.com\/www.biocloudservice.com\/wordpress\/wp-content\/uploads\/2023\/10\/word-image-16101-1.png?resize=768%2C240 768w, https:\/\/i0.wp.com\/www.biocloudservice.com\/wordpress\/wp-content\/uploads\/2023\/10\/word-image-16101-1.png?resize=600%2C187 600w\" sizes=\"(max-width: 640px) 100vw, 640px\" data-recalc-dims=\"1\" \/><\/p>\n<p>\u5b83\u80fd\u591f\u5904\u7406\u5927\u578b\u591a\u7ef4\u6570\u636e\u96c6\u5e76\u4e14\u80fd\u9ad8\u6548\u5730\u8ba1\u7b97\u5e76\u663e\u793a\u805a\u7c7b\u5206\u6790\u7684\u7ed3\u679c\u3002\u6b64\u5916\uff0c\u5b83\u5177\u6709\u4e00\u4e2a\u5f3a\u5927\u7684\u56fe\u5f62\u7528\u6237\u754c\u9762\u4f7f\u5f97\u5b83\u5bf9\u4e8e\u521d\u5b66\u8005\u4e5f\u6613\u4e8e\u4f7f\u7528\u3002<\/p>\n<p><strong>dropClust<\/strong> \u5728\u4ee5\u4e0b\u65b9\u9762\u5177\u6709\u7279\u8272\uff1a<\/p>\n<ul>\n<li><strong>\u9ad8\u6548\u4e14\u7075\u6d3b\u7684\u7b97\u6cd5<\/strong>\uff1a\u4f7f\u7528\u9ad8\u6548\u7684\u8ba1\u7b97\u7b97\u6cd5\u6765\u5904\u7406\u5927\u578b\u591a\u7ef4\u6570\u636e\u96c6\uff0c\u5e76\u4e14\u80fd\u591f\u81ea\u7531\u8c03\u6574\u805a\u7c7b\u6570\u76ee\u548c\u5176\u5b83\u5173\u952e\u53c2\u6570\u3002<\/li>\n<li><strong>\u53ef\u6269\u5c55\u6027<\/strong>\uff1a\u8ba1\u7b97\u548c\u5185\u5b58\u4f7f\u7528\u6548\u7387\u9ad8\uff0c\u53ef\u4ee5\u5728\u5e38\u89c4\u4e2a\u4eba\u7535\u8111\u6216\u5c0f\u578b\u670d\u52a1\u5668\u4e0a\u8fd0\u884c\uff0c\u65e0\u9700\u7279\u6b8a\u7684\u786c\u4ef6\u914d\u7f6e\u3002<\/li>\n<li><strong>\u6570\u636e\u53ef\u89c6\u5316<\/strong>\uff1a\u901a\u8fc7\u591a\u79cd\u56fe\u5f62\u8f93\u51fa\u65b9\u5f0f\uff0c\u7528\u6237\u53ef\u4ee5\u76f4\u89c2\u5730\u67e5\u770b\u548c\u7406\u89e3\u805a\u7c7b\u7ed3\u679c\u3002<\/li>\n<li><strong>\u7528\u6237\u53cb\u597d\u7684\u754c\u9762<\/strong>\uff1a\u5177\u6709\u7b80\u6d01\u660e\u4e86\u7684\u56fe\u5f62\u7528\u6237\u754c\u9762\uff0c\u4f7f\u5f97\u8be5\u8f6f\u4ef6\u6613\u4e8e\u4f7f\u7528\uff0c\u5373\u4f7f\u662f\u5bf9\u4e8e\u6ca1\u6709\u7f16\u7a0b\u7ecf\u9a8c\u7684\u4eba\u4e5f\u662f\u5982\u6b64\u3002<\/li>\n<li><strong>\u5e7f\u6cdb\u7684\u5e94\u7528\u9886\u57df<\/strong>\uff1a\u9002\u7528\u4e8e\u5404\u79cd\u7fa4\u4f53\u9057\u4f20\u5b66\u7814\u7a76\u9886\u57df\uff0c\u4f8b\u5982\u4eba\u7c7b\u9057\u4f20\u5b66\u3001\u52a8\u690d\u7269\u9057\u4f20\u5b66\u3001\u5fae\u751f\u7269\u57fa\u56e0\u7ec4\u5b66\u7b49\u3002<\/li>\n<\/ul>\n<h2>1\u5b89\u88c5<\/h2>\n<p>\u4e0b\u9762\u5c0f\u82b1\u6765\u6559\u4f60\u5982\u4f55\u8fdb\u884c\u5b89\u88c5\u5427~<\/p>\n<p>R\u8f6f\u4ef6\u5305\u7684\u5f00\u53d1\u7248\u672c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0bR\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<p>library(devtools)<br \/>\ninstall_github(&#8220;debsin\/dropClust&#8221;, dependencies = T)<\/p>\n<h2>2\u4f7f\u7528\u793a\u4f8b<\/h2>\n<p>\u5c0f\u82b1\u901a\u8fc7\u4e00\u4e2a\u4f8b\u5b50\u6559\u4f1a\u4f60\u5982\u4f55\u4f7f\u7528\u5b83\u5427~<\/p>\n<p>\u5c0f\u82b1\u4f7f\u7528 10X \u7f51\u7ad9\u4e0a\u7684\u4e00\u4e2a\u5c0f\u6570\u636e\u96c6\uff08\u6b64\u5904\u4e3a 3K PBMC \u6570\u636e\u96c6\uff09\u6765\u6f14\u793a\u6807\u51c6\u7ba1\u9053\u3002<\/p>\n<h3>2.1\u8bbe\u7f6e\u76ee\u5f55<\/h3>\n<p>library(dropClust)<br \/>\nset.seed(0)<\/p>\n<h3>2.2\u52a0\u8f7d\u6570\u636e<\/h3>\n<p>dropClust\u4ece\u4e09\u4e2a\u8f93\u5165\u6587\u4ef6\u4e2d\u52a0\u8f7dUMI\u8ba1\u6570\u8868\u8fbe\u6570\u636e\u3002\u8fd9\u4e9b\u6587\u4ef6\u4e0e10X\u7f51\u7ad9\u4e0a\u53ef\u7528\u7684\u6570\u636e\u96c6\u91c7\u7528\u76f8\u540c\u7684\u7ed3\u6784\uff0c\u5373\uff1a<\/p>\n<ul>\n<li>\u4ee5\u7a00\u758f\u683c\u5f0f\u8ba1\u7b97\u77e9\u9635\u6587\u4ef6\u4e2d\u7684\u8ba1\u6570<\/li>\n<li>\u4ee5TSV\u6587\u4ef6\u5f62\u5f0f\u63d0\u4f9b\u8f6c\u5f55\u7ec4\u6807\u8bc6\u7b26<\/li>\n<li>\u4ee5TSV\u6587\u4ef6\u5f62\u5f0f\u63d0\u4f9b\u57fa\u56e0\u6807\u8bc6\u7b26<\/li>\n<\/ul>\n<p># \u52a0\u8f7d\u6570\u636e\uff0c\u8def\u5f84\u5305\u542b\u89e3\u538b\u6587\u4ef6<br \/>\nsce &lt;-readfiles(path = &#8220;C:\/Projects\/dropClust\/data\/pbmc3k\/hg19\/&#8221;)<\/p>\n<h3>2.3\u9884\u5904\u7406<\/h3>\n<p>dropClust\u6267\u884c\u9884\u5904\u7406\u4ee5\u53bb\u9664\u8d28\u91cf\u8f83\u5dee\u7684\u7ec6\u80de\u548c\u57fa\u56e0\u3002dropClust\u8fd8\u53ef\u4ee5\u51cf\u8f7b\u53ef\u80fd\u5b58\u5728\u7684\u6279\u6b21\u6548\u5e94\u3002\u7528\u6237\u65e0\u9700\u63d0\u4f9b\u6709\u5173\u5404\u4e2a\u8f6c\u5f55\u7ec4\u6279\u6b21\u6765\u6e90\u7684\u4efb\u4f55\u4fe1\u606f\u3002\u4f46\u662f\uff0c\u6279\u6b21\u6548\u5e94\u6d88\u9664\u6b65\u9aa4\u662f\u53ef\u9009\u62e9\u7684\u3002<br \/>\n\u6839\u636e\u53c2\u6570min_count\u6307\u5b9a\u7684\u7ec6\u80de\u4e2d\u603bUMI\u8ba1\u6570\u5bf9\u7ec6\u80de\u8fdb\u884c\u8fc7\u6ee4\u3002\u6839\u636e\u7ed9\u5b9a\u9608\u503cmin_count\u4ee5\u4e0a\u8868\u8fbe\u7684\u7ec6\u80de\u7684\u6700\u5c0f\u6570\u91cfmin_count\uff0c\u5220\u9664\u8d28\u91cf\u8f83\u5dee\u7684\u57fa\u56e0\u3002<\/p>\n<p># \u8fc7\u6ee4\u8d28\u91cf\u8f83\u5dee\u7684\u5355\u5143\u683c\u3002 \u9608\u503c th \u76f8\u5f53\u4e8e\u5355\u5143\u683c\u7684\u603b\u8ba1\u6570\u3002<br \/>\nsce&lt;-FilterCells(sce)<br \/>\nsce&lt;-FilterGenes(sce)<\/p>\n<h4>2.3.1\u6570\u636e\u6807\u51c6\u5316\u548c\u53bb\u9664\u4f4e\u8d28\u91cf\u57fa\u56e0<\/h4>\n<p>\u7136\u540e\u4ec5\u5bf9\u9ad8\u8d28\u91cf\u57fa\u56e0\u8fdb\u884c\u8ba1\u6570\u5f52\u4e00\u5316\u3002\u5728SingleCellExperiment\u5bf9\u8c61\u4e2d\u4f7f\u7528\u539f\u59cb\u8ba1\u6570\u6570\u636e\u8ba1\u7b97\u5f52\u4e00\u5316\u8868\u8fbe\u503c\uff0c\u4f7f\u7528\u4e2d\u4f4d\u6570\u5f52\u4e00\u5316\u603b\u8ba1\u6570\u3002<\/p>\n<p>sce&lt;-CountNormalize(sce)<\/p>\n<h4>2.3.2\u9009\u62e9\u9ad8\u53d8\u5f02\u57fa\u56e0<\/h4>\n<p>\u901a\u8fc7\u6839\u636e\u57fa\u56e0\u7684\u79bb\u6563\u5ea6\u6307\u6570\u5bf9\u5176\u8fdb\u884c\u6392\u540d\u6765\u8fdb\u884c\u8fdb\u4e00\u6b65\u57fa\u56e0\u9009\u62e9\u3002<\/p>\n<p># \u901a\u8fc7\u8bbe\u7f6e ngenes_keep\uff0c\u9009\u62e9\u9876\u7ea7\u5206\u6563\u57fa\u56e0\u3002<br \/>\nsce&lt;-RankGenes(sce, ngenes_keep = 1000)<\/p>\n<h3>2.4\u7ed3\u6784\u4fdd\u6301\u53d6\u6837<\/h3>\n<p>\u9996\u5148\u4ee5\u5feb\u901f\u7684\u65b9\u5f0f\u6267\u884c\u805a\u7c7b\u4ee5\u4f30\u8ba1\u6570\u636e\u7684\u7c97\u7565\u7ed3\u6784\u3002\u7136\u540e\u5bf9\u8fd9\u4e9b\u805a\u7c7b\u4e2d\u7684\u6bcf\u4e00\u4e2a\u8fdb\u884c\u91c7\u6837\u4ee5\u5fae\u8c03\u805a\u7c7b\u8fc7\u7a0b\u3002<\/p>\n<p>sce&lt;-Sampling(sce)<\/p>\n<h3>2.5\u57fa\u4e8e PCA \u7684\u57fa\u56e0\u9009\u62e9<\/h3>\n<p>\u53e6\u4e00\u79cd\u57fa\u56e0\u9009\u62e9\u662f\u4e3a\u4e86\u964d\u4f4e\u7ef4\u5ea6\u6570\u91cf\u3002PCA\u88ab\u7528\u6765\u8bc6\u522b\u5f71\u54cd\u4e3b\u8981\u6210\u5206\u7684\u57fa\u56e0\u3002<\/p>\n<p># Find PCA top 200 genes. This may take some time.<br \/>\nsce&lt;-RankPCAGenes(sce)<\/p>\n<h3>2.6\u805a\u7c7b\u5206\u6790<\/h3>\n<h4>2.6.1\u5fae\u8c03\u805a\u7c7b\u8fc7\u7a0b<\/h4>\n<p>\u9ed8\u8ba4\u60c5\u51b5\u4e0b\uff0c\u8fd4\u56de\u7684\u662f\u57fa\u4e8eLouvain\u7b97\u6cd5\u7684\u6700\u4f73\u62df\u5408\u805a\u7c7b\u3002\u4f46\u662f\uff0c\u7528\u6237\u53ef\u4ee5\u8c03\u6574\u53c2\u6570\u4ee5\u751f\u6210\u6240\u9700\u6570\u91cf\u7684\u805a\u7c7b\u3002\u672a\u91c7\u6837\u7684\u8f6c\u5f55\u7ec4\u88ab\u5206\u914d\u4ece\u7cbe\u7ec6\u8c03\u6574\u805a\u7c7b\u6240\u4ea7\u751f\u7684\u6807\u8bc6\u7b26\u4e2d\u83b7\u5f97\u805a\u7c7b\u6807\u8bc6\u7b26\u3002\u540e\u9a8c\u8d4b\u503c\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6e\u4fe1\u5fc3\u503c\u201cconf\u201d\u6765\u63a7\u5236\u3002\u8f83\u9ad8\u7684\u201cconf\u201d\u503c\u5c06\u4ec5\u5411\u5171\u4eab\u5927\u591a\u6570\u6700\u8fd1\u90bb\u5c45\u7684\u8f6c\u5f55\u7ec4\u5206\u914d\u805a\u7c7b\u6807\u8bc6\u7b26\u3002<\/p>\n<p># \u5f53 `method = hclust` \u65f6<br \/>\n# \u4f7f\u7528\u53c2\u6570 minClusterSize \u8c03\u6574\u6700\u5c0f\u805a\u7c7b\u5927\u5c0f\uff08\u9ed8\u8ba4\u503c = 20\uff09<br \/>\n# \u4f7f\u7528\u53c2\u6570 level deepSplit\uff08\u9ed8\u8ba4\u503c = 3\uff09\u8c03\u6574\u6811\u5207\u5272\uff0c\u6570\u503c\u8d8a\u5927\uff0c\u4ea7\u751f\u7684\u805a\u7c7b\u8d8a\u591a\u3002<br \/>\nsce&lt;-Cluster(sce, method = &#8220;default&#8221;, conf = 0.8)<\/p>\n<h3>2.7\u53ef\u89c6\u5316\u805a\u7c7b\u7ed3\u679c<\/h3>\n<p>\u4e3a\u6837\u54c1\u8ba1\u7b972D\u5d4c\u5165\uff0c\u7136\u540e\u8fdb\u884c\u4e8b\u540e\u805a\u7c7b\u3002<\/p>\n<p>sce&lt;-PlotEmbedding(sce, embedding = &#8220;umap&#8221;, spread = 10, min_dist = 0.1)<\/p>\n<p>plot_data = data.frame(&#8220;Y1&#8243; = reducedDim(sce,&#8221;umap&#8221;)[,1], Y2 = reducedDim(sce, &#8220;umap&#8221;)[,2], color = sce$ClusterIDs)<\/p>\n<p>ScatterPlot(plot_data,title = &#8220;Clusters&#8221;)<\/p>\n<h3>2.8\u627e\u5230\u7279\u5b9a\u7c07\u4e2d\u5dee\u5f02\u8868\u8fbe\u7684\u57fa\u56e0<\/h3>\n<p>DE_genes_all = FindMarkers(sce, selected_clusters=NA, lfc_th = 1, q_th =0.001, nDE=30)<\/p>\n<p>write.csv(DE_genes_all$genes,<br \/>\nfile = file.path(tempdir(),&#8221;ct_genes.csv&#8221;),<br \/>\nquote = FALSE)<\/p>\n<h3>2.9\u7ed8\u5236\u624b\u5de5\u6311\u9009\u7684\u6807\u8bb0\u57fa\u56e0\u56fe<\/h3>\n<p>marker_genes = c(&#8220;S100A8&#8221;, &#8220;GNLY&#8221;, &#8220;PF4&#8221;)<\/p>\n<p>p&lt;-PlotMarkers(sce, marker_genes)<\/p>\n<h3>2.10\u6bcf\u4e2a\u805a\u7c7b\u524d DE \u57fa\u56e0\u7684\u70ed\u56fe<\/h3>\n<p># Draw heatmap<br \/>\np&lt;-PlotHeatmap(sce, DE_res = DE_genes_all$DE_res,nDE = 10)<\/p>\n<p>print(p)<\/p>\n<p>\u4ee5\u4e0a\u5c31\u662f\u5c0f\u82b1\u5e26\u4f60\u5b66\u4e60\u7684\u5168\u90e8\uff0c\u5feb\u52a8\u624b\u7528\u8d77\u6765\u5427~\u5b83\u8fd8\u6709\u5728\u7ebf\u5de5\u5177\uff0c\u662f\u7f16\u7a0b\u5c0f\u767d\u7684\u5206\u6790\u5229\u5668\u3002<\/p>\n<p>\u5982\u679c\u5c0f\u4f19\u4f34\u6709\u5176\u4ed6\u6570\u636e\u5206\u6790\u9700\u6c42\uff0c\u53ef\u4ee5\u5c1d\u8bd5\u4f7f\u7528\u672c\u516c\u53f8\u65b0\u5f00\u53d1\u7684\u751f\u4fe1\u5206\u6790\u5c0f\u5de5\u5177\u4e91\u5e73\u53f0\uff0c\u96f6\u4ee3\u7801\u5b8c\u6210\u5206\u6790\uff0c\u975e\u5e38\u65b9\u4fbf\u5965\uff0c\u4e91\u5e73\u53f0\u7f51\u5740\u4e3a\uff1a(<a href=\"http:\/\/www.biocloudservice.com\/home.html\">http:\/\/www.biocloudservice.com\/home.html<\/a>)\uff0c\u5176\u4e2d\u4e5f\u5305\u62ec\u4e86\u901a\u8def\u8868\u8fbe\u5206\u6790(<a href=\"http:\/\/www.biocloudservice.com\/313\/313.php\">http:\/\/www.biocloudservice.com\/313\/313.php<\/a>)\uff0c\u5355\u7ec6\u80de\u7684\u57fa\u56e0\u5171\u8868\u8fbe\u5206\u6790(<a href=\"http:\/\/www.biocloudservice.com\/906\/906.php\">http:\/\/www.biocloudservice.com\/906\/906.php<\/a>)\u7b49\u5404\u79cd\u5c0f\u5de5\u5177\u54e6~\uff0c\u6709\u5174\u8da3\u7684\u5c0f\u4f19\u4f34\u53ef\u4ee5\u767b\u5f55\u7f51\u7ad9\u8fdb\u884c\u4e86\u89e3\u3002<\/p>\n<h2>\u53c2\u8003\u6587\u732e<\/h2>\n<p>Debajyoti Sinha, Pradyumn Sinha, Ritwik Saha, Sanghamitra Bandyopadhyay, Debarka Sengupta, Improved <em>dropClust<\/em> R package with integrative analysis support for scRNA-seq data, <em>Bioinformatics<\/em>, Volume 36, Issue 6, March 2020, Pages 1946\u20131947, <a href=\"https:\/\/doi.org\/10.1093\/bioinformatics\/btz823\">https:\/\/doi.org\/10.1093\/bioinformatics\/btz823<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u4eca\u5929\u5c0f\u82b1\u7ed9\u5927\u5bb6\u4ecb\u7ecd\u4e00\u4e2a\u7b80\u5355\u597d\u7528\u7684\u751f\u4fe1\u5206\u6790\u5de5\u5177\u7bb1\u2014\u2014dropClust \u662f\u4e00\u4e2a\u7528\u4e8e\u5728\u5168\u57fa\u56e0\u7ec4\u5c3a\u5ea6\u9274\u5b9a\u5e76\u53ef\u89c6\u5316\u7fa4\u4f53 [&hellip;]<\/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\/16101"}],"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=16101"}],"version-history":[{"count":1,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/16101\/revisions"}],"predecessor-version":[{"id":16103,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/16101\/revisions\/16103"}],"wp:attachment":[{"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=16101"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=16101"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=16101"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}