{"id":61287,"date":"2024-10-28T15:01:26","date_gmt":"2024-10-28T07:01:26","guid":{"rendered":"http:\/\/www.biocloudservice.com\/wordpress\/?p=61287"},"modified":"2024-10-28T15:01:26","modified_gmt":"2024-10-28T07:01:26","slug":"%e5%9f%ba%e5%9b%a0%e8%a1%a8%e8%be%be%e5%88%86%e6%9e%90%e7%bb%93%e6%9e%9c%e4%b8%8d%e6%98%8e%e7%a1%ae%ef%bc%9f%e5%88%ab%e6%8b%85%e5%bf%83%ef%bc%8csva%e5%8c%85%e6%9d%a5%e5%b8%ae%e4%bd%a0%ef%bc%81","status":"publish","type":"post","link":"http:\/\/www.biocloudservice.com\/wordpress\/?p=61287","title":{"rendered":"\u57fa\u56e0\u8868\u8fbe\u5206\u6790\u7ed3\u679c\u4e0d\u660e\u786e\uff1f\u522b\u62c5\u5fc3\uff0cSVA\u5305\u6765\u5e2e\u4f60\uff01\u7cbe\u51c6\u6821\u6b63\u9690\u85cf\u7684\u6df7\u6742\u56e0\u7d20\uff0c\u8ba9\u4f60\u7684\u6570\u636e\u5206\u6790\u66f4\u9760\u8c31\uff01"},"content":{"rendered":"\n
\"\"<\/figure>\n\n\n\n

\u5927\u5bb6\u597d\uff01\u4eca\u5929\u5c0f\u5e08\u59b9\u8981\u5411\u5927\u5bb6\u4ecb\u7ecd\u4e00\u4e2a\u5728\u57fa\u56e0\u7ec4\u5b66\u7814\u7a76\u4e2d\u975e\u5e38\u91cd\u8981\u7684R\u5305\u2014\u2014SVA\u5305\uff01SVA\uff08Surrogate Variable Analysis\uff09\u5305\u662f\u4e00\u4e2a\u4e13\u95e8\u7528\u4e8e\u6821\u6b63\u57fa\u56e0\u8868\u8fbe\u6570\u636e\u4e2d\u7684\u6279\u6b21\u6548\u5e94\u548c\u9690\u85cf\u6df7\u6742\u56e0\u7d20\u7684\u5f3a\u5927\u5de5\u5177\u3002\u968f\u7740RNA-seq\u548c\u5fae\u9635\u5217\u7b49\u9ad8\u901a\u91cf\u57fa\u56e0\u7ec4\u6280\u672f\u7684\u53d1\u5c55\uff0c\u5982\u4f55\u51cf\u5c11\u975e\u751f\u7269\u5b66\u56e0\u7d20\u5bf9\u5206\u6790\u7ed3\u679c\u7684\u5f71\u54cd\u53d8\u5f97\u81f3\u5173\u91cd\u8981\uff0c\u800cSVA\u5305\u6070\u597d\u80fd\u5e2e\u52a9\u6211\u4eec\u89e3\u51b3\u8fd9\u4e2a\u95ee\u9898\u3002\u5b83\u901a\u8fc7\u4f30\u8ba1\u66ff\u4ee3\u53d8\u91cf\uff0c\u6709\u6548\u53bb\u9664\u6280\u672f\u56e0\u7d20\u5bf9\u5dee\u5f02\u8868\u8fbe\u5206\u6790\u7684\u5e72\u6270\uff0c\u663e\u8457\u63d0\u5347\u5206\u6790\u7684\u51c6\u786e\u6027\u3002\u5c0f\u5e08\u59b9\u53ef\u662fSVA\u5305\u7684\u5fe0\u5b9e\u7c89\u4e1d\uff0c\u5982\u679c\u5927\u5bb6\u6709\u6821\u6b63\u57fa\u56e0\u8868\u8fbe\u6570\u636e\u7684\u56f0\u6270\uff0c\u968f\u65f6\u53ef\u4ee5\u8054\u7cfb\u6211\u54e6\uff01<\/strong><\/strong><\/p>\n\n\n\n

\u5728\u672c\u6b21\u5b66\u4e60\u4e2d\uff0c\u6211\u4eec\u4e0d\u4ec5\u4f1a\u5b66\u4f1a\u5982\u4f55\u5b89\u88c5\u548c\u4f7f\u7528SVA\u5305\uff0c\u8fd8\u5c06\u638c\u63e1\u5982\u4f55\u5904\u7406\u8180\u80f1\u764c\u7684\u57fa\u56e0\u8868\u8fbe\u6570\u636e\u3001\u4f30\u8ba1\u548c\u6821\u6b63\u6df7\u6742\u53d8\u91cf\uff0c\u4ee5\u53ca\u7ed3\u5408limma\u5305\u8fdb\u884c\u6821\u6b63\u540e\u7684\u5dee\u5f02\u8868\u8fbe\u5206\u6790\u3002\u901a\u8fc7\u5b9e\u9645\u793a\u4f8b\u7684\u64cd\u4f5c\uff0c\u6211\u4eec\u5c06\u6df1\u5165\u4e86\u89e3\u5982\u4f55\u4f7f\u7528SVA\u5305\u6765\u6d88\u9664\u6279\u6b21\u6548\u5e94\uff0c\u4ece\u800c\u83b7\u5f97\u66f4\u53ef\u9760\u7684\u7814\u7a76\u7ed3\u679c\u3002\u76f8\u4fe1\u901a\u8fc7\u4eca\u5929\u7684\u5b66\u4e60\uff0c\u540c\u5b66\u4eec\u80fd\u591f\u66f4\u52a0\u719f\u7ec3\u5730\u5e94\u7528SVA\u5305\uff0c\u4e3a\u81ea\u5df1\u7684\u57fa\u56e0\u7ec4\u5b66\u7814\u7a76\u6253\u4e0b\u575a\u5b9e\u7684\u57fa\u7840\uff01\u63a5\u4e0b\u6765\uff0c\u8bf7\u540c\u5b66\u4eec\u8ddf\u7d27\u5c0f\u5e08\u59b9\u7684\u6b65\u4f10\uff0c\u6b63\u5f0f\u5f00\u542fSVA\u5305\u7684\u5b66\u4e60\u4e4b\u65c5\u5427\uff01<\/p>\n\n\n\n

\u672c\u6b21\u4ecb\u7ecd\u7684R\u5305\u5728\u670d\u52a1\u5668\u4e0a\u80fd\u66f4\u52a0\u6d41\u7545\u5730\u8fd0\u884c\uff0c\u5982\u679c\u6ca1\u6709\u670d\u52a1\u5668\uff0c\u6b22\u8fce\u8054\u7cfb\u6211\u4eec\u8fdb\u884c\u670d\u52a1\u5668\u79df\u8d41~<\/strong><\/strong><\/p>\n\n\n\n

sva\u5305\u4ecb\u7ecd<\/p>\n\n\n\n

SVA\uff08Surrogate Variable Analysis\uff09\u5305\u662fR\u8bed\u8a00\u4e2d\u7528\u4e8e\u6821\u6b63\u57fa\u56e0\u8868\u8fbe\u6570\u636e\u4e2d\u6279\u6b21\u6548\u5e94\u548c\u9690\u85cf\u6df7\u6742\u56e0\u7d20\u7684\u5de5\u5177\u3002\u5b83\u901a\u8fc7\u4f30\u8ba1\u672a\u89c2\u6d4b\u5230\u7684\u66ff\u4ee3\u53d8\u91cf\uff08Surrogate Variables\uff09\uff0c\u51cf\u5c11\u975e\u751f\u7269\u5b66\u56e0\u7d20\uff08\u5982\u6280\u672f\u6279\u6b21\u6216\u5b9e\u9a8c\u6761\u4ef6\uff09\u5bf9\u5206\u6790\u7ed3\u679c\u7684\u5f71\u54cd\uff0c\u4ece\u800c\u63d0\u9ad8\u5dee\u5f02\u8868\u8fbe\u5206\u6790\u7684\u51c6\u786e\u6027\u3002SVA \u53ef\u4ee5\u5728\u672a\u660e\u786e\u77e5\u9053\u6df7\u6742\u56e0\u7d20\u7684\u60c5\u51b5\u4e0b\u6709\u6548\u8c03\u6574\u6570\u636e\uff0c\u5e38\u7528\u4e8eRNA-seq\u3001\u5fae\u9635\u5217\u7b49\u9ad8\u901a\u91cf\u57fa\u56e0\u7ec4\u5b66\u7814\u7a76\uff0c\u5e2e\u52a9\u7814\u7a76\u8005\u907f\u514d\u5047\u9633\u6027\u7ed3\u679c\uff0c\u63d0\u9ad8\u7ed3\u679c\u7684\u53ef\u4fe1\u5ea6\u3002<\/p>\n\n\n\n

sva\u5305\u5b89\u88c5<\/p>\n\n\n\n

\u9700\u8981R\u8bed\u8a00\u7248\u672c\u4e3a4.4\uff0c\u5728\u63a7\u5236\u53f0\u4e2d\u8f93\u5165\u4ee5\u4e0b\u547d\u4ee4\uff1a<\/p>\n\n\n\n

if (!require(“BiocManager”, quietly = TRUE))<\/p>\n\n\n\n

    install.packages(“BiocManager”)<\/p>\n\n\n\n

BiocManager::install(“sva”) #\u5728BiocManager\u73af\u5883\u4e0b\u5b89\u88c5sva\u5305<\/p>\n\n\n\n

\u67e5\u770b\u662f\u5426\u5b89\u88c5\u6210\u529f\uff1a<\/p>\n\n\n\n

packageVersion(“sva”) # \u67e5\u770bsva\u7248\u672c<\/p>\n\n\n\n

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

\u663e\u793a\u4e3a3.52.0\u7248\u672c\uff0c\u5219\u8868\u793a\u5df2\u7ecf\u5b89\u88c5\u4e86sva\u5305\u3002<\/p>\n\n\n\n

\u9664\u6b64\u4e4b\u5916\uff0c\u540e\u7eed\u793a\u4f8b\u8fd8\u9700\u8981\u4f7f\u7528bladderbatch, limma\uff0c\u8fd9\u4e24\u4e2aR\u5305\uff0c\u6211\u4eec\u53ef\u4ee5\u63d0\u524d\u5b89\u88c5\uff0c\u5b89\u88c5\u547d\u4ee4\u5982\u4e0b\uff1a<\/p>\n\n\n\n

BiocManager::install(“bladderbatch”) # \u5728BiocManager\u73af\u5883\u4e0b\u5b89\u88c5bladderbatch<\/p>\n\n\n\n

BiocManager::install(“limma”) # \u5728BiocManager\u73af\u5883\u4e0b\u5b89\u88c5limma<\/p>\n\n\n\n

\u4f7f\u7528sva\u5305\u6821\u6b63\u9ad8\u901a\u91cf\u57fa\u56e0\u8868\u8fbe\u6570\u636e\u4e2d\u7684\u6df7\u6742\u6548\u5e94\u3002<\/p>\n\n\n\n

\u8f7d\u5165\u9700\u8981\u7684\u5305\u548c\u6570\u636e<\/strong><\/strong><\/p>\n\n\n\n

\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u8f7d\u5165\u672c\u6b21\u5b66\u4e60\u7684\u4e3b\u89d2\u2014\u2014Bio3D\u5305\uff0c\u4ee5\u53ca\u5176\u4f59\u4e24\u4e2a\u9700\u8981\u7528\u5230\u7684R\u5305\uff0c\u76f8\u5173\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n\n\n\n

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

# \u52a0\u8f7d SVA \u5305\uff0c\u7528\u4e8e\u5904\u7406\u6279\u6b21\u6548\u5e94\u548c\u4f30\u8ba1\u66ff\u4ee3\u53d8\u91cf\u3002<\/p>\n\n\n\n

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

# \u52a0\u8f7d bladderbatch \u6570\u636e\u5305\uff0c\u5176\u4e2d\u5305\u542b\u8180\u80f1\u764c\u7684\u57fa\u56e0\u8868\u8fbe\u6570\u636e\u96c6\u3002<\/p>\n\n\n\n

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

# \u52a0\u8f7d limma \u5305\uff0c\u7528\u4e8e\u5dee\u5f02\u8868\u8fbe\u5206\u6790\u4e2d\u7684\u7ebf\u6027\u6a21\u578b\u62df\u5408\u3002<\/p>\n\n\n\n

\u5728\u672c\u6587\u4e2d\u6211\u4eec\u4f7f\u7528bladderbatch\u5305\u4e2d\u7684\u8180\u80f1\u764c\u76f8\u5173\u6570\u636e\u4f5c\u4e3a\u793a\u4f8b\uff0c\u5173\u6ce8\u70b9\u662f\u764c\u75c7\u72b6\u6001\u7684\u57fa\u56e0\u8868\u8fbe\u5dee\u5f02\u3002\u8f7d\u5165\u6570\u636e\u7684\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n\n\n\n

data(bladderdata)<\/p>\n\n\n\n

# \u4ece bladderbatch \u5305\u4e2d\u52a0\u8f7d\u8180\u80f1\u764c\u6570\u636e\u96c6 bladderdata\u3002<\/p>\n\n\n\n

bladderEset<\/p>\n\n\n\n

# \u67e5\u770bbladderEset\u6570\u636e\u96c6\u7684\u6570\u636e\u7279\u5f81<\/p>\n\n\n\n

\u663e\u793a\u7ed3\u679c\u5982\u4e0b\u56fe<\/p>\n\n\n\n

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

\u7531\u56fe\u53ef\u77e5\uff0c\u8be5\u6570\u636e\u96c6\u5305\u542b\u670957\u4e2a\u6837\u672c\u768422283\u4e2a\u6570\u636e\u7279\u5f81\u3002<\/p>\n\n\n\n

\u63d0\u53d6\u8868\u578b\u6570\u636e\u5e76\u521b\u5efa\u6a21\u578b\u77e9\u9635<\/strong><\/strong><\/p>\n\n\n\n

\u5728\u8180\u80f1\u764c\u7814\u7a76\u4e2d\uff0c\u764c\u75c7\u72b6\u6001\u662f\u6211\u4eec\u7684\u4e3b\u8981\u5173\u6ce8\u70b9\u3002\u6570\u636e\u5b58\u50a8\u5728 ExpressionSet \u5bf9\u8c61\u4e2d\uff0c\u8be5\u5bf9\u8c61\u5305\u542b\u57fa\u56e0\u8868\u8fbe\u6570\u636e\u548c\u6837\u672c\u7684\u8868\u578b\u4fe1\u606f\u3002<\/p>\n\n\n\n

\u56e0\u6b64\u6211\u4eec\u9700\u8981\u4ece ExpressionSet \u5bf9\u8c61\u7684\u8868\u578b\u6570\u636e\u69fd\u4e2d\u63d0\u53d6\u8868\u578b\u4fe1\u606f\uff0c\u5e76\u83b7\u53d6\u57fa\u56e0\u8868\u8fbe\u77e9\u9635\uff0c\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n\n\n\n

pheno = pData(bladderEset)<\/p>\n\n\n\n

# \u4ece bladderEset \u5bf9\u8c61\u4e2d\u63d0\u53d6\u8868\u578b\u6570\u636e\uff08\u6837\u672c\u4fe1\u606f\uff09\uff0c\u5b58\u50a8\u5728 pheno \u53d8\u91cf\u4e2d\u3002<\/p>\n\n\n\n

edata = exprs(bladderEset)<\/p>\n\n\n\n

# \u4ece bladderEset \u5bf9\u8c61\u4e2d\u63d0\u53d6\u57fa\u56e0\u8868\u8fbe\u6570\u636e\u77e9\u9635\uff0c\u5b58\u50a8\u5728 edata \u53d8\u91cf\u4e2d\u3002<\/p>\n\n\n\n

\u968f\u540e\u6211\u4eec\u9700\u8981\u4f7f\u7528\u63d0\u53d6\u5230\u7684\u6570\u636e\u521b\u5efa\u6a21\u578b\u77e9\u9635\uff0c\u5305\u62ec\u5168\u6a21\u578b\u548c\u7a7a\u6a21\u578b\u3002\u5168\u6a21\u578b\uff1a\u5305\u542b\u611f\u5174\u8da3\u7684\u53d8\u91cf\uff08\u764c\u75c7\u72b6\u6001\uff09\uff0c\u764c\u75c7\u72b6\u6001\u662f\u591a\u6c34\u5e73\u53d8\u91cf\uff0c\u56e0\u6b64\u7528\u56e0\u5b50\u5904\u7406\u3002\u7a7a\u6a21\u578b\uff1a\u4ec5\u5305\u542b\u622a\u8ddd\uff0c\u56e0\u4e3a\u6ca1\u6709\u5176\u4ed6\u8c03\u6574\u53d8\u91cf\u3002<\/p>\n\n\n\n

mod = model.matrix(~as.factor(cancer), data=pheno)<\/p>\n\n\n\n

# \u521b\u5efa\u5168\u6a21\u578b\u77e9\u9635<\/p>\n\n\n\n

mod0 = model.matrix(~1, data=pheno)<\/p>\n\n\n\n

# \u521b\u5efa\u7a7a\u6a21\u578b\u77e9\u9635<\/p>\n\n\n\n

\u4f7f\u7528 SVA \u5305\u4f30\u8ba1\u66ff\u4ee3\u53d8\u91cf<\/strong><\/strong><\/p>\n\n\n\n

\u9996\u5148\u6211\u4eec\u9700\u8981\u4f7f\u7528num.sv\uff08\uff09\u51fd\u6570\u6765\u4f30\u8ba1\u66ff\u4ee3\u53d8\u91cf\u6570\u91cf\uff0c\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n\n\n\n

n.sv = num.sv(edata, mod, method=”leek”)<\/p>\n\n\n\n

# \u4f7f\u7528 Leek \u65b9\u6cd5\u4f30\u8ba1\u66ff\u4ee3\u53d8\u91cf\uff08surrogate variables, SV\uff09\u7684\u6570\u91cf\u3002\u8fd9\u91cc\u662f\u901a\u8fc7\u57fa\u56e0\u8868\u8fbe\u6570\u636e\uff08edata\uff09\u548c\u5168\u6a21\u578b\uff08mod\uff09\u6765\u786e\u5b9a\u7684\u3002<\/p>\n\n\n\n

\u8f93\u51fa\u66ff\u4ee3\u53d8\u91cf\u6570\u91cf\uff08n.sv\uff09\uff0c\u4f8b\u5982 n.sv = 2\uff0c\u8868\u793a\u6709 2 \u4e2a\u9690\u85cf\u6df7\u6742\u56e0\u5b50\u3002\u63a5\u7740\u6211\u4eec\u4f7f\u7528 sva\uff08\uff09\u51fd\u6570\uff1a\u8bc4\u4f30\u66ff\u4ee3\u53d8\u91cf\u3002<\/p>\n\n\n\n

svobj = sva(edata, mod, mod0, n.sv=n.sv)<\/p>\n\n\n\n

# \u4f7f\u7528 SVA \u5305\u4e2d\u7684 sva \u51fd\u6570\u6765\u4f30\u8ba1\u66ff\u4ee3\u53d8\u91cf\u3002\u8f93\u5165\u7684\u57fa\u56e0\u8868\u8fbe\u6570\u636e\u662f edata\uff0c\u5168\u6a21\u578b\u662f mod\uff0c\u7a7a\u6a21\u578b\u662f mod0\uff0c<\/p>\n\n\n\n

\u6821\u6b63\u540e\u8ba1\u7b97 F \u68c0\u9a8c p \u503c<\/strong><\/strong><\/p>\n\n\n\n

\u63a5\u4e0b\u6765\u6211\u4eec\u4f7f\u7528f.pvalue\uff08\uff09\u51fd\u6570\u8ba1\u7b97\u6570\u636e\u77e9\u9635\u6bcf\u4e00\u884c\u7684\u53c2\u6570F\u6765\u68c0\u9a8cp\u503c\u3002F\u68c0\u9a8c\u6bd4\u8f83\u7684\u662f\u5d4c\u5957\u6a21\u578b\uff0c\u56e0\u6b64mod\u548cmod0\u4e2d\u6240\u6709\u7684\u53d8\u91cf\u90fd\u5fc5\u987b\u5728mod\u4e2d\u51fa\u73b0\u3002\u9996\u5148\uff0c\u6211\u4eec\u53ef\u4ee5\u5728\u4e0d\u8c03\u6574\u66ff\u4ee3\u53d8\u91cf\u7684\u60c5\u51b5\u4e0b\u8ba1\u7b97\u4e0e\u764c\u75c7\u72b6\u6001\u76f8\u5173\u7684\u5dee\u5f02\u8868\u8fbe\u7684F\u68c0\u9a8cp\u503c\uff0c\u7136\u540e\u5bf9\u5b83\u4eec\u8fdb\u884c\u591a\u91cd\u68c0\u9a8c\u6821\u6b63\uff0c\u5e76\u8ba1\u7b97\u5728Q\u503c\u5c0f\u4e8e0.05\u7684\u60c5\u51b5\u4e0b\u663e\u8457\u7684\u57fa\u56e0\u6570\u91cf\u3002<\/p>\n\n\n\n

\u4e0d\u8c03\u6574\u66ff\u4ee3\u53d8\u91cf\u7684 p \u503c\uff1a<\/p>\n\n\n\n

pValues = f.pvalue(edata, mod, mod0)<\/p>\n\n\n\n

# \u4f7f\u7528 f.pvalue \u51fd\u6570\u8ba1\u7b97 F \u68c0\u9a8c\u7684 p \u503c\u3002<\/p>\n\n\n\n

qValues = p.adjust(pValues, method=”BH”)<\/p>\n\n\n\n

# \u4f7f\u7528 Benjamini-Hochberg (BH) \u65b9\u6cd5\u5bf9 p \u503c\u8fdb\u884c\u591a\u91cd\u68c0\u9a8c\u6821\u6b63\uff0c\u751f\u6210\u6821\u6b63\u540e\u7684 q \u503c\u3002<\/p>\n\n\n\n

\u8c03\u6574\u66ff\u4ee3\u53d8\u91cf\u540e\u7684 p \u503c\uff1a\u5728\u6a21\u578b\u4e2d\u52a0\u5165\u66ff\u4ee3\u53d8\u91cf\u3002<\/p>\n\n\n\n

modSv = cbind(mod, svobj$sv)<\/p>\n\n\n\n

# \u5c06\u4f30\u8ba1\u7684\u66ff\u4ee3\u53d8\u91cf\uff08svobj$sv\uff09\u4e0e\u5168\u6a21\u578b\uff08mod\uff09\u7ed3\u5408\uff0c\u521b\u5efa\u4e00\u4e2a\u5305\u542b\u6821\u6b63\u66ff\u4ee3\u53d8\u91cf\u7684\u6a21\u578b modSv\u3002<\/p>\n\n\n\n

mod0Sv = cbind(mod0, svobj$sv)<\/p>\n\n\n\n

# \u540c\u6837\u5730\uff0c\u5c06\u66ff\u4ee3\u53d8\u91cf\u4e0e\u7a7a\u6a21\u578b\uff08mod0\uff09\u7ed3\u5408\uff0c\u521b\u5efa\u4e00\u4e2a\u5305\u542b\u6821\u6b63\u66ff\u4ee3\u53d8\u91cf\u7684\u7a7a\u6a21\u578b mod0Sv\u3002<\/p>\n\n\n\n

pValuesSv = f.pvalue(edata, modSv, mod0Sv)<\/p>\n\n\n\n

# \u4f7f\u7528\u6821\u6b63\u4e86\u66ff\u4ee3\u53d8\u91cf\u7684\u5168\u6a21\u578b\u548c\u7a7a\u6a21\u578b\u8ba1\u7b97\u65b0\u7684 F \u68c0\u9a8c p \u503c\u3002<\/p>\n\n\n\n

qValuesSv = p.adjust(pValuesSv, method=”BH”)<\/p>\n\n\n\n

# \u5bf9\u6821\u6b63\u6df7\u6742\u6548\u5e94\u540e\u8ba1\u7b97\u7684 p \u503c\u518d\u6b21\u4f7f\u7528 Benjamini-Hochberg (BH) \u65b9\u6cd5\u8fdb\u884c\u591a\u91cd\u68c0\u9a8c\u6821\u6b63\uff0c\u751f\u6210\u6821\u6b63\u540e\u7684 q \u503c\u3002<\/p>\n\n\n\n

head(qValuesSv, n=20) # \u67e5\u770b\u77eb\u6b63\u4e4b\u540e\u7684q\u503c\u7ed3\u679c<\/p>\n\n\n\n

\u663e\u793a\u7ed3\u679c\u5982\u4e0b\u56fe\uff1a<\/p>\n\n\n\n

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

\u7ed3\u5408limma\u5305\u8fdb\u884c\u5dee\u5f02\u8868\u8fbe\u5206\u6790<\/strong><\/strong><\/p>\n\n\n\n

limma \u5305\u662f\u5dee\u5f02\u8868\u8fbe\u5206\u6790\u4e2d\u6700\u5e38\u7528\u7684\u5305\u4e4b\u4e00\u3002sva \u5305\u53ef\u4ee5\u5f88\u65b9\u4fbf\u5730\u4e0e limma \u5305\u7ed3\u5408\u4f7f\u7528\uff0c\u4ee5\u6267\u884c\u6821\u6b63\u540e\u7684\u5dee\u5f02\u8868\u8fbe\u5206\u6790\u3002<\/p>\n\n\n\n

\u8fd9\u4e2a\u8fc7\u7a0b\u7684\u7b2c\u4e00\u6b65\u662f\u62df\u5408\u5305\u542b\u66ff\u4ee3\u53d8\u91cf\u7684\u7ebf\u6027\u6a21\u578b\uff0c\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n\n\n\n

fit = lmFit(edata, modSv)  # \u4f7f\u7528\u5305\u542b\u66ff\u4ee3\u53d8\u91cf\u7684\u6a21\u578b\u77e9\u9635 modSv \u5bf9\u8868\u8fbe\u6570\u636e edata \u8fdb\u884c\u7ebf\u6027\u62df\u5408<\/p>\n\n\n\n

\u968f\u540e\uff0c\u6784\u5efa\u5b9a\u4e49\u764c\u75c7\u72b6\u6001\u4e4b\u95f4\u7684\u5bf9\u6bd4\u77e9\u9635<\/p>\n\n\n\n

contrast.matrix <- cbind(<\/p>\n\n\n\n

  “C1” = c(-1,1,0,rep(0,svobj$n.sv)),  # \u521b\u5efa\u5bf9\u6bd4\u77e9\u9635 C1\uff0c\u7528\u4e8e\u6bd4\u8f83\u4e0d\u540c\u6761\u4ef6\uff08\u4f8b\u5982\u6761\u4ef61 vs \u6761\u4ef62\uff09<\/p>\n\n\n\n

  “C2” = c(0,-1,1,rep(0,svobj$n.sv)),  # \u521b\u5efa\u5bf9\u6bd4\u77e9\u9635 C2\uff0c\u7528\u4e8e\u6bd4\u8f83\u4e0d\u540c\u6761\u4ef6\uff08\u4f8b\u5982\u6761\u4ef62 vs \u6761\u4ef63\uff09<\/p>\n\n\n\n

  “C3” = c(-1,0,1,rep(0,svobj$n.sv))   # \u521b\u5efa\u5bf9\u6bd4\u77e9\u9635 C3\uff0c\u7528\u4e8e\u6bd4\u8f83\u4e0d\u540c\u6761\u4ef6\uff08\u4f8b\u5982\u6761\u4ef61 vs \u6761\u4ef63\uff09<\/p>\n\n\n\n

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

fitContrasts = contrasts.fit(fit, contrast.matrix)  # \u5e94\u7528\u5bf9\u6bd4\u77e9\u9635\u8fdb\u884c\u5dee\u5f02\u8868\u8fbe\u5206\u6790\uff0c\u66f4\u65b0\u7ebf\u6027\u62df\u5408\u6a21\u578b<\/p>\n\n\n\n

\u6700\u540e\uff0c\u4f7f\u7528 eBayes \u8ba1\u7b97\u68c0\u9a8c\u7edf\u8ba1\u91cf\uff1a<\/p>\n\n\n\n

eb = eBayes(fitContrasts)  # \u4f7f\u7528\u8d1d\u53f6\u65af\u65b9\u6cd5\u6765\u63d0\u9ad8\u7edf\u8ba1\u5206\u6790\u7684\u7a33\u5b9a\u6027<\/p>\n\n\n\n

topTableF(eb, adjust=”BH”)  # \u8f93\u51fa F \u7edf\u8ba1\u91cf\u7684\u524d\u51e0\u4e2a\u7ed3\u679c\uff0c\u5e76\u4f7f\u7528 Benjamini-Hochberg \u65b9\u6cd5\u8fdb\u884c\u591a\u91cd\u68c0\u9a8c\u6821\u6b63<\/p>\n\n\n\n

\u663e\u793a\u7ed3\u679c\u5982\u4e0b\u56fe\uff0c<\/p>\n\n\n\n

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

\u56fe\u4e2d\uff0c207783_x_at \u57fa\u56e0\u5728 C1 \u5bf9\u6bd4\u4e0b\u6709 -13.45607 \u7684 log2 fold change\uff0cC2 \u5bf9\u6bd4\u4e0b\u6709 0.26592438\uff0c\u800c C3 \u5bf9\u6bd4\u4e0b\u4e3a -13.19015\u3002\u8fd9\u610f\u5473\u7740\u8be5\u57fa\u56e0\u5728\u4e0d\u540c\u6761\u4ef6\u4e4b\u95f4\u5b58\u5728\u8f83\u5927\u7684\u5dee\u5f02\u8868\u8fbe\u3002\u5176 F \u7edf\u8ba1\u91cf\u4e3a 8622.518\uff0c\u539f\u59cb p \u503c\u6781\u5c0f\uff081.207560e-69\uff09\uff0c\u7ecf\u8fc7\u6821\u6b63\u540e\u7684 p \u503c\u4e5f\u662f\u6781\u5c0f\u7684\uff081.419991e-65\uff09\uff0c\u8bf4\u660e\u8fd9\u4e2a\u57fa\u56e0\u5728\u8fd9\u4e9b\u6761\u4ef6\u4e0b\u6709\u975e\u5e38\u663e\u8457\u7684\u5dee\u5f02\u8868\u8fbe\u3002<\/p>\n\n\n\n

\u4ee5\u4e0a\u5c31\u662f\u5bf9SVA\u5305\u7684\u4ecb\u7ecd\u3002\u901a\u8fc7\u672c\u6587\uff0c\u6211\u4eec\u4e86\u89e3\u4e86SVA\u5305\u5728\u6821\u6b63\u57fa\u56e0\u8868\u8fbe\u6570\u636e\u4e2d\u7684\u6df7\u6742\u6548\u5e94\u548c\u6279\u6b21\u6548\u5e94\u65b9\u9762\u7684\u5e94\u7528\u3002SVA\u5305\u901a\u8fc7\u4f30\u8ba1\u66ff\u4ee3\u53d8\u91cf\u6765\u6d88\u9664\u975e\u751f\u7269\u5b66\u56e0\u7d20\u7684\u5f71\u54cd\uff0c\u4ece\u800c\u63d0\u9ad8\u5dee\u5f02\u8868\u8fbe\u5206\u6790\u7684\u51c6\u786e\u6027\u3002\u540c\u65f6\uff0c\u7ed3\u5408limma\u5305\u53ef\u4ee5\u8fdb\u4e00\u6b65\u8fdb\u884c\u6821\u6b63\u540e\u7684\u5dee\u5f02\u8868\u8fbe\u5206\u6790\uff0c\u51c6\u786e\u8bc6\u522b\u51fa\u663e\u8457\u5dee\u5f02\u8868\u8fbe\u7684\u57fa\u56e0\u3002\u5e0c\u671b\u5927\u5bb6\u5728\u5b66\u4e60\u548c\u4f7f\u7528SVA\u5305\u65f6\uff0c\u80fd\u591f\u719f\u7ec3\u638c\u63e1\u5176\u57fa\u672c\u64cd\u4f5c\uff0c\u901a\u8fc7\u4e0d\u65ad\u7684\u5b9e\u8df5\u548c\u63a2\u7d22\uff0c\u5728\u9ad8\u901a\u91cf\u57fa\u56e0\u7ec4\u5b66\u7814\u7a76\u4e2d\u53d6\u5f97\u66f4\u5927\u7684\u8fdb\u5c55\u548c\u6210\u679c\u3002<\/p>\n\n\n\n

\u540c\u5b66\u4eec\u5982\u679c\u89c9\u5f97\u81ea\u5df1\u5199\u4ee3\u7801\u9ebb\u70e6\uff0c\u53ef\u4ee5\u4f53\u9a8c\u4e00\u4e0b\u6211\u4eec\u7684\u4e91\u751f\u4fe1\u5c0f\u5de5\u5177\uff0c\u53ea\u9700\u8f93\u5165\u6570\u636e\uff0c\u5373\u53ef\u8f7b\u677e\u751f\u6210\u6240\u9700\u56fe\u8868\u3002\u7acb\u5373\u8bbf\u95ee\u4e91\u751f\u4fe1\uff08<\/a><\/strong>http:\/\/www.biocloudservice.com\/home.html<\/u><\/a>\uff09\uff0c\u5f00\u542f\u4fbf\u6377\u7684\u751f\u4fe1\u4e4b\u65c5\uff01<\/strong><\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"

\u5927\u5bb6\u597d\uff01\u4eca\u5929\u5c0f\u5e08\u59b9\u8981\u5411\u5927\u5bb6\u4ecb\u7ecd\u4e00\u4e2a\u5728\u57fa\u56e0\u7ec4\u5b66\u7814\u7a76\u4e2d\u975e\u5e38\u91cd\u8981\u7684R\u5305\u2014\u2014SVA\u5305\uff01SVA\uff08Surrogate Va […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"","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\/61287"}],"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=61287"}],"version-history":[{"count":1,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/61287\/revisions"}],"predecessor-version":[{"id":61293,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/61287\/revisions\/61293"}],"wp:attachment":[{"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=61287"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=61287"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.biocloudservice.com\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=61287"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}