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r - 我如何编写自己的函数来自动计算 R 中的临床特征和基因

问题描述

我正在尝试在 R 中编写自己的函数，其作用是自动计算基因与感兴趣的临床特征之间的相关性。这是我的代码行：

#Empty data.frame
cc1 <- data.frame(Estimate=paste("Site", 1:35), P.value="")
estimates = numeric(35)
pvalues = numeric(35)

#compute correlation between clinical feature and genes
computeCC = function(x)
{
  if (x = ""){
  for (i in 1:35) {
      cc<-cor.test(cor[,i], cor[,x],    
                   method = "spearman")
      estimates[i] = cc$estimate
      pvalues[i] = cc$p.value
      cc1$Estimate <- estimates
      cc1$P.value <- pvalues
      rownames(cc1) = colnames(cor)[1:35]}}}

其中，cor是一个数据框，包括1904名患者和38列（35个基因+“lymph”、“npi”和“stage”）；“lymph”、“npi”和“stage”是cor中的列名，分别是三个临床特征，即阳性淋巴结数、诺丁汉预后指数和肿瘤分期。

我想写一个函数，这样当我写类似的东西时：

computeCC(lymph)

它将显示淋巴结数量与 35 个基因中的每一个之间的相关系数和 p 值。

同样，当我写：computeCC(stage)

它将显示肿瘤阶段与 35 个基因中的每一个之间的相关系数和 p 值。

但是现在，我遇到了一个问题：

错误：意外的 '}' 在：“cc1$P.value <- pvalues rownames(cc1) = colnames(cor)[1:35]}}”

这是我的可重现数据：

cor <-  structure(list(NCOR1 = c(0.6488, 0.3312, -0.3336, 0.2663, -1.3986), ZFP36L1 = c(-1.4278, -1.9684, -1.4047, -1.1984, 0.397), SMAD4 = c(-0.5692, -2.5897, -1.4175, -2.2613, 0.6804), CDKN1B = c(-0.9829, -1.7246, -1.1409, -1.5033, -0.8475), CDH1 = c(-0.1387, 1.5924, -0.7637, 1.2737, 0.5298), PIK3R1 = c(0.2649, -0.2267, -0.6875, -0.8364, 1.3622), BRCA2 = c(0.6442, 1.2209, -0.6712, -1.0785, -0.296), KMT2C = c(-0.8759, -0.327, -0.0154, -0.7076, -0.0817), KRAS = c(0.5975, -0.0729, 0.0069, -1.3664, -0.9904), MUC16 = c(0.4375, -0.7318, -0.5569, -0.8224, -0.3882), CBFB = c(-0.9757, 0.9849, -0.9263, -1.7691, -0.7777), MAP2K4 = c(0.385, -0.6192, -1.5389, -0.1092, -2.4083), AHNAK2 = c(0.69, 0.2453, -0.0492, -1.0581, -0.2553), BAP1 = c(0.0535, -3.1571, 1.8473, -0.2338, -0.9715), ERBB2 = c(0.6171,4.4808, -0.643, 0.496, 1.1611), TP53 = c(-0.065, 1.3605, -0.0393, 1.6328, -0.3413), MAP3K1 = c(-1.241, -0.6619, -1.4874, -2.1246, 2.2862), ERBB3 = c(0.7237, -0.1072, -0.2926, -1.1115,0.5288), PTEN = c(-0.4454, -1.2554, -0.9175, -0.6936, -0.0996
), PIK3CA = c(-1.9252, -2.2674, -0.0451, -0.6883, -1.0361
), GPS2 = c(0.489, -0.363, 0.1914, -0.1519, 0.237), SF3B1 = c(1.0353, 
1.0428, 0.1198, -0.1978, 1.3932), AGTR2 = c(0.395, 1.7066, 
0.2963, 0.5277, 0.5876), SYNE1 = c(0.1814, -0.8717, -0.3925, 
-0.6181, 0.2515), GATA3 = c(0.727, -0.1693, 0.1266, 0.2467, 
0.7005), AKT1 = c(0.7579, 1.9675, -1.0293, -1.1985, -1.902
), FOXO3 = c(-0.1501, 0.0589, -0.3752, -0.4585, -0.8405), 
ARID1A = c(0.7732, -0.695, 0.0034, -0.9322, 0.5824), RB1 = c(-0.135, 
-0.6994, 0.487, 1.7919, 0.9048), CDKN2A = c(0.0647, 0.1072, 
-0.3117, -0.2668, -0.6555), MEN1 = c(-0.5376, 2.164, 1.2287, 
0.5037, 0.7852), NF1 = c(-0.5943, -0.2639, -0.8211, 0.2209, 
1.5184), TBX3 = c(-0.765, -0.2696, 0.1784, 0.6917, 0.3603
), CHEK2 = c(-0.5534, 1.8462, -0.8928, 0.7362, -0.3503), 
RUNX1 = c(-0.8007, -1.9473, 0.6226, -0.6965, 0.1434), lymph = c(1, 
5, 8, 1, 0), npi = c(4.036, 6.032, 6.03, 5.042, 3.046), stage = c(2, 
2, 3, 2, 2)), row.names = c("MB-0362", "MB-0346", "MB-0386", "MB-0574", "MB-0503"), class = "data.frame")

谁能给我一个想法？提前致谢。

标签： rfunction

解决方案

尝试这个。你的代码有很多问题。我已经对它进行了最低限度的修改，以（我认为）得到你想要的。

computeCC = function(data, var) # Pass the data and a variable
{
  var <- eval(substitute(var), data, parent.frame()) # This may confuse you

  for (i in 1:35) {
    cc <- cor.test(data[,i], var, method = "spearman")
    estimates[i] = cc$estimate
    pvalues[i] = cc$p.value
  }

# These belong outside the loop
  cc1$Estimate <- estimates
  cc1$P.value <- pvalues
  rownames(cc1) = colnames(cor)[1:35]
  cc1
}

然后调用它并保存结果：

cc2 <- computeCC(cor, lymph)

然后在cc2中查看结果。

还可以进行其他更改来改进代码，但一次只做一步。

您提供的数据：

cc1 <- data.frame(Estimate=paste("Site", 1:35), P.value="")
estimates = numeric(35)
pvalues = numeric(35)

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