{"id":65840,"date":"2026-10-10T14:00:37","date_gmt":"2026-10-10T06:00:37","guid":{"rendered":"https:\/\/www.biocloudservice.com\/wordpress\/?post_type=ftc_question&p=65840"},"modified":"2026-10-10T14:00:37","modified_gmt":"2026-10-10T06:00:37","slug":"counts-tpm-normalized-matrix-input","status":"publish","type":"ftc_question","link":"https:\/\/www.biocloudservice.com\/wordpress\/ferroptosis\/questions\/counts-tpm-normalized-matrix-input\/","title":{"rendered":"count\u3001TPM\u3001\u6807\u51c6\u5316\u77e9\u9635\u5206\u522b\u80fd\u7528\u4e8e\u54ea\u4e9b\u94c1\u6b7b\u4ea1\u5206\u6790\uff1f"},"content":{"rendered":"

\u5148\u770b\u7ed3\u8bba\uff1a<\/strong>\u5148\u786e\u8ba4\u77e9\u9635\u7684\u6d4b\u91cf\u5355\u4f4d\u548c\u751f\u6210\u8fc7\u7a0b\uff0c\u518d\u9009\u62e9\u65b9\u6cd5\u3002DESeq2 \u7684\u5e38\u89c4\u8ba1\u6570\u6a21\u578b\u9700\u8981\u672a\u5f52\u4e00\u5316\u7684 counts \u6216\u53d7\u652f\u6301\u7684\u5b9a\u91cf\u5bfc\u5165\u6d41\u7a0b\uff0c\u4e0d\u80fd\u628a TPM \u6216 log \u8868\u8fbe\u56db\u820d\u4e94\u5165\u540e\u5145\u5f53 counts\u3002\u8bc4\u5206\u548c\u53ef\u89c6\u5316\u53ef\u4ee5\u4f7f\u7528\u9002\u914d\u65b9\u6cd5\u7684\u8868\u8fbe\u91cf\uff0c\u4f46\u4ecd\u9700\u8bb0\u5f55\u53d8\u6362\u3001\u8f93\u5165\u5c42\u548c\u57fa\u56e0\u8986\u76d6\u3002<\/p>\n

\u9002\u7528\u60c5\u51b5<\/h2>\n

\u62ff\u5230\u4e00\u4e2a\u540d\u79f0\u542b expression\u3001normalized\u3001counts \u6216 TPM \u7684\u6587\u4ef6\uff0c\u4e0d\u6e05\u695a\u80fd\u5426\u505a\u5dee\u5f02\u8868\u8fbe\u3001GSVA\u3001ssGSEA \u6216\u5355\u7ec6\u80de\u8bc4\u5206\u3002<\/p>\n

\u5efa\u8bae\u6309\u8fd9\u4e2a\u987a\u5e8f\u68c0\u67e5<\/h2>\n
    \n
  1. \u67e5\u539f\u59cb\u8bf4\u660e\u3001\u811a\u672c\u6216\u6570\u636e\u4e0b\u8f7d\u5b57\u6bb5\uff0c\u8bb0\u5f55\u5e73\u53f0\u3001\u5355\u4f4d\u3001\u662f\u5426\u53d6\u5bf9\u6570\u548c\u662f\u5426\u5df2\u7ecf\u505a\u6279\u6b21\u5904\u7406\u3002<\/li>\n
  2. \u6838\u5bf9\u884c\u5217\u542b\u4e49\u3001\u57fa\u56e0 ID\u3001\u6837\u672c ID\u3001\u91cd\u590d\u540d\u79f0\u3001\u7f3a\u5931\u503c\u548c\u6570\u503c\u8303\u56f4\uff1b\u4e0d\u80fd\u4ec5\u51ed\u6574\u6570\u5916\u89c2\u8ba4\u5b9a\u4e3a\u539f\u59cb counts\u3002<\/li>\n
  3. \u8ba1\u6570\u5dee\u5f02\u5206\u6790\u4f7f\u7528\u53d7\u652f\u6301\u7684\u539f\u59cb\u8ba1\u6570\u6216\u5b9a\u91cf\u5bfc\u5165\u8def\u5f84\uff1b\u4e0d\u8981\u7528 TPM\u3001FPKM \u6216\u7ecf\u8fc7\u6821\u6b63\u7684\u8fde\u7eed\u503c\u4f2a\u88c5 counts\u3002<\/li>\n
  4. \u6837\u672c\u8bc4\u5206\u6309\u6240\u7528\u65b9\u6cd5\u548c\u7248\u672c\u9009\u62e9\u8f93\u5165\u4e0e\u53c2\u6570\uff1b\u82af\u7247\u6807\u51c6\u5316\u503c\u3001log \u8868\u8fbe\u548c\u5355\u7ec6\u80de\u5c42\u4e0d\u662f\u53ef\u968f\u610f\u66ff\u6362\u7684\u5bf9\u8c61\u3002<\/li>\n
  5. \u6bcf\u5f20\u7ed3\u679c\u8868\u9644\u4e0a\u8f93\u5165\u7c7b\u578b\u3001\u53d8\u6362\u3001\u8f6f\u4ef6\u7248\u672c\u548c\u5bf9\u7167\u65b9\u5411\uff0c\u4ee5\u4fbf\u68c0\u67e5\u65b9\u5411\u6216\u5c3a\u5ea6\u5dee\u5f02\u3002<\/li>\n<\/ol>\n

    \u8f93\u5165\u4e0e\u4efb\u52a1\u5bf9\u7167\u8868<\/h2>\n
    \n\n\n\n\n\n\n\n\n
    \u8f93\u5165<\/th>\n\u5e38\u89c1\u7528\u9014<\/th>\n\u9700\u8981\u907f\u5f00\u7684\u64cd\u4f5c<\/th>\n<\/tr>\n<\/thead>\n
    \u672a\u5f52\u4e00\u5316\u57fa\u56e0 counts<\/td>\n\u8ba1\u6570\u6a21\u578b\u5dee\u5f02\u5206\u6790\uff1b\u4e4b\u540e\u53e6\u4f5c\u53d8\u6362<\/td>\n\u5148\u8f6c TPM \u518d\u8fd0\u884c\u5e38\u89c4 DESeq2<\/td>\n<\/tr>\n
    TPM \/ FPKM<\/td>\n\u63cf\u8ff0\u8868\u8fbe\uff1b\u6309\u65b9\u6cd5\u8981\u6c42\u53d8\u6362\u540e\u8bc4\u5206<\/td>\n\u56db\u820d\u4e94\u5165\u5f53\u6210\u539f\u59cb\u8ba1\u6570<\/td>\n<\/tr>\n
    \u82af\u7247\u6807\u51c6\u5316\u8868\u8fbe<\/td>\n\u5339\u914d\u8bbe\u8ba1\u7684 limma \u5206\u6790\u6216\u8bc4\u5206<\/td>\n\u5957\u7528\u6d4b\u5e8f\u6587\u5e93\u5927\u5c0f\u5f52\u4e00\u5316<\/td>\n<\/tr>\n
    Seurat data \/ scale.data \u7b49\u5c42<\/td>\n\u4f9d\u65b9\u6cd5\u4f7f\u7528\u6307\u5b9a\u5c42<\/td>\n\u628a\u7f29\u653e\u6b8b\u5dee\u5f53\u7edd\u5bf9\u8868\u8fbe\u6216 counts<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

    \u4f9d\u636e\uff1aDESeq2 \u5b98\u65b9\u6559\u7a0b\uff1a\u8f93\u5165\u3001\u8bbe\u8ba1\u77e9\u9635\u4e0e\u6280\u672f\u91cd\u590d<\/a> \u00b7 Bioconductor\uff1alimma \u8f6f\u4ef6\u4ecb\u7ecd\u4e0e\u7528\u6237\u6307\u5357\u5165\u53e3<\/a> \u00b7 Seurat v5\uff1aassay\u3001layer \u4e0e\u6570\u636e\u8bbf\u95ee<\/a><\/p>\n

    \u4e00\u4e2a\u201c\u770b\u8d77\u6765\u6b63\u786e\u201d\u4f46\u4f1a\u51fa\u9519\u7684\u4f8b\u5b50<\/h2>\n

    \u793a\u610f\u60c5\u5883\uff1a\u4e0b\u8f7d\u7684\u8868\u8fbe\u8868\u5168\u662f\u5c0f\u6570\uff0c\u8fd0\u884c DESeq2 \u540e\u63d0\u793a\u4e0d\u662f\u6574\u6570\u3002\u5148\u56de\u5230\u6570\u636e\u6765\u6e90\u786e\u8ba4\u5355\u4f4d\uff1b\u5982\u679c\u662f TPM\uff0c\u5c31\u4e0d\u80fd\u7528 round() \u6d88\u9664\u62a5\u9519\u540e\u7ee7\u7eed\u89e3\u91ca\u4e3a\u8ba1\u6570\u5206\u6790\u3002\u82e5\u539f\u59cb\u6587\u4ef6\u6765\u81ea Salmon \u7b49\u5b9a\u91cf\u5de5\u5177\uff0c\u5e94\u67e5\u53d7\u652f\u6301\u7684 tximport \u7b49\u5bfc\u5165\u8def\u5f84\uff0c\u4e0d\u80fd\u628a\u5168\u90e8\u5c0f\u6570\u8f93\u5165\u4e00\u6982\u5224\u6210\u975e\u6cd5\u3002<\/p>\n

    \u53e6\u4e00\u4e2a\u5e38\u89c1\u95ee\u9898\u662f\u5bf9\u5df2\u7ecf log2 \u53d8\u6362\u7684\u82af\u7247\u77e9\u9635\u518d\u6b21 log2\u3002\u6570\u503c\u8303\u56f4\u53ea\u80fd\u5e2e\u52a9\u53d1\u73b0\u7591\u70b9\uff0c\u771f\u6b63\u7684\u4f9d\u636e\u5e94\u662f\u539f\u59cb\u5904\u7406\u8bb0\u5f55\u3002\u6765\u6e90\u65e0\u6cd5\u786e\u8ba4\u65f6\uff0c\u628a\u8f93\u5165\u6807\u8bb0\u4e3a\u201c\u5355\u4f4d\u5f85\u786e\u8ba4\u201d\u3002<\/p>\n

    \u4f9d\u636e\uff1aDESeq2 \u5b98\u65b9\u6559\u7a0b\uff1a\u8f93\u5165\u3001\u8bbe\u8ba1\u77e9\u9635\u4e0e\u6280\u672f\u91cd\u590d<\/a><\/p>\n

    \u5148\u68c0\u67e5\u6837\u672c\u662f\u5426\u5bf9\u9f50<\/h2>\n

    \u6b64\u68c0\u67e5\u53ef\u53d1\u73b0\u6837\u672c\u96c6\u5408\u548c\u987a\u5e8f\u95ee\u9898\uff0c\u4e0d\u80fd\u8bc1\u660e\u6587\u4ef6\u5355\u4f4d\u6b63\u786e\u3002\u6b63\u5f0f\u6d41\u7a0b\u8fd8\u9700\u6838\u5bf9\u91cd\u590d\u751f\u7269\u6837\u672c\u3001\u4f9b\u4f53\u548c\u6279\u6b21\u3002<\/p>\n

    # \u4eba\u5de5\u6784\u9020\u793a\u4f8b\uff1b\u771f\u5b9e\u5206\u6790\u5fc5\u987b\u63d0\u4f9b sample_id \u5217\nx <- matrix(c(10, 20, 12, 18), nrow = 2,\n            dimnames = list(c('DEMO_A','DEMO_B'), c('S1','S2')))\nmeta <- data.frame(sample_id = c('S2','S1'), group = c('case','control'))\nstopifnot(!anyDuplicated(colnames(x)), !anyDuplicated(meta$sample_id))\nstopifnot(setequal(colnames(x), meta$sample_id))\nmeta <- meta[match(colnames(x), meta$sample_id), , drop = FALSE]\nstopifnot(identical(colnames(x), meta$sample_id))<\/code><\/pre>\n
    \u4e0d\u80fd\u4ece\u5f53\u524d\u7ed3\u679c\u76f4\u63a5\u5f97\u51fa\u4ec0\u4e48<\/h2>\n
    \u201c\u6807\u51c6\u5316\u77e9\u9635\u201d\u4e0d\u662f\u4e00\u4e2a\u8db3\u591f\u660e\u786e\u7684\u6570\u636e\u7c7b\u578b\u3002GSVA \u7b49\u65b9\u6cd5\u4e5f\u5e76\u975e\u4e00\u5f8b\u62d2\u7edd counts\uff0c\u662f\u5426\u4f7f\u7528\u7279\u5b9a\u8ba1\u6570\u5206\u5e03\u6216\u8f6c\u6362\u5fc5\u987b\u6309\u5f53\u524d\u65b9\u6cd5\u8bf4\u660e\u51b3\u5b9a\uff1b\u8fd9\u4e0e DESeq2 \u7684\u8f93\u5165\u8981\u6c42\u662f\u4e0d\u540c\u95ee\u9898\u3002<\/p>\n
    \u4f9d\u636e\u4e0e\u7248\u672c<\/h2>\n