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我正在尝试针对我的控件（R247、R235、R241）标准化矩阵中的值。

我coldata的是：

        Condition  Tank
R235      Control    T6
R236  LowExposure    T6
R239 HighExposure    T6
R241      Control    T8
R242  LowExposure    T8
R245 HighExposure    T8
R247      Control T14_3
R248  LowExposure T14_3
R250 HighExposure T14_3

和我的矩阵mydata：

                       R235      R236      R239      R241      R242      R245     R247      R248      R250
ENSDARG00000033160 11.91873 10.899929 10.831388 12.092478 11.564555 10.908011 11.67680 11.168115 10.414632
ENSDARG00000013522 12.39036 11.692673 11.439107 12.440952 11.841307 11.118888 12.13594 11.634806 11.336330
ENSDARG00000103295 10.54697 10.004169  8.753556 10.659075  9.980232  8.511240 11.11711 10.690518  9.240825
ENSDARG00000056765  9.18106  8.488917  7.431641  9.440119  8.830816  7.901337 10.39879  9.899546  8.142807
ENSDARG00000087303 11.07447 10.765197 11.682291 11.010172 10.380666 11.487207 11.05384 10.526109 11.962465
ENSDARG00000018478 11.51562 11.000702 10.382845 11.597848 11.218944 10.185381 11.61043 11.214280 10.614338

我通过以下方式提取控制样本：

x <- which(coldata$Condition %in% "Control")
control <- row.names(coldata[x,])

与 z-score 转换类似，我想使用均值和 sd 但仅来自对照组来转换数据集，例如(x - mean[control]) / sd[control]，如下所示：

function(x){
(x - rowMeans[,control])/apply(matrix[,control],1,sd)
}

然后用它apply()来运行它mydata：apply(mydata, 1, function(x))但我不知道如何正确地把它写成一个可以通过apply使用的函数。非常感谢任何帮助。谢谢！

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2 回答 2

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也许你可以试试下面的代码

ctr<-c(mydata[,control])
mydata <- (mydata - mean(ctr))/sd(ctr)

这样

> mydata
                         R235       R236       R239       R241         R242       R245       R247
ENSDARG00000033160  0.7649126 -0.3416566 -0.4161023  0.9536287  0.380225962 -0.3328783  0.5021407
ENSDARG00000013522  1.2771728  0.5193811  0.2439708  1.3321233  0.680819738 -0.1038346  1.0008349
ENSDARG00000103295 -0.7250225 -1.3145850 -2.6729365 -0.6032598 -1.340584125 -2.9361276 -0.1057658
ENSDARG00000056765 -2.2086036 -2.9603737 -4.1087325 -1.9272271 -2.589020615 -3.5985729 -0.8859680
ENSDARG00000087303 -0.1520791 -0.4879955  0.5081047 -0.2219163 -0.905653327  0.2962145 -0.1744864
ENSDARG00000018478  0.3270753 -0.2322021 -0.9032866  0.4163871  0.004841085 -1.1177618  0.4300530
                            R248       R250
ENSDARG00000033160 -0.0503667586 -0.8687612
ENSDARG00000013522  0.4565289817  0.1323397
ENSDARG00000103295 -0.5691080347 -2.1436899
ENSDARG00000056765 -1.4282211043 -3.3363006
ENSDARG00000087303 -0.7476806273  0.8124153
ENSDARG00000018478 -0.0002247121 -0.6518508

数据

 coldata <- structure(list(Condition = c("Control", "LowExposure", "HighExposure", 
"Control", "LowExposure", "HighExposure", "Control", "LowExposure", 
"HighExposure"), Tank = c("T6", "T6", "T6", "T8", "T8", "T8", 
"T14_3", "T14_3", "T14_3")), class = "data.frame", row.names = c("R235", 
"R236", "R239", "R241", "R242", "R245", "R247", "R248", "R250"
))

mydata <- structure(c(0.764912614946124, 1.27717284283513, -0.725022482925137, 
-2.20860361193701, -0.152079137057719, 0.327075283851119, -0.341656586405671, 
0.519381138288775, -1.31458498734254, -2.96037370907202, -0.487995549202655, 
-0.232202141300273, -0.416102292318654, 0.243970801913007, -2.67293645010139, 
-4.10873247484514, 0.508104744323286, -0.90328660925782, 0.95362874851536, 
1.3321232689093, -0.603259802757428, -1.92722706172457, -0.221916314787733, 
0.416387104598013, 0.380225961822725, 0.680819737852109, -1.34058412453691, 
-2.58902061521661, -0.905653326889375, 0.00484108465005354, -0.332878334043016, 
-0.103834591964374, -2.93612761559372, -3.59857285819956, 0.296214545867932, 
-1.11776184119785, 0.502140702783651, 1.00083493562074, -0.105765764038217, 
-0.885967971059041, -0.174486381086619, 0.430053025314037, -0.0503667586240605, 
0.456528981709989, -0.569108034749636, -1.42822110426138, -0.747680627262844, 
-0.000224712061085116, -0.868761206158128, 0.132339715167575, 
-2.14368994546163, -3.33630057435765, 0.812415320598279, -0.651850829229599
), .Dim = c(6L, 9L), .Dimnames = list(c("ENSDARG00000033160", 
"ENSDARG00000013522", "ENSDARG00000103295", "ENSDARG00000056765", 
"ENSDARG00000087303", "ENSDARG00000018478"), c("R235", "R236", 
"R239", "R241", "R242", "R245", "R247", "R248", "R250")))
于 2020-01-20T11:01:39.707 回答
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@ThomasIsCoding 非常感谢您的帮助！我通过以下方式对其进行了整理：

ctrM <- apply(mydata[,control], 1, FUN = mean)
Sd <- apply(mydata, 1, FUN = sd)
new <- (mydata - ctrM)/Sd #centering around ctrM and scaling with Sd

抱歉，我没有提供有关我的数据结构的信息，但现在可以使用了：) 我还意识到，为了缩放行，我需要对整行使用整体 Sd，而不仅仅是平均值。因此，我以行的 Sd 的控制和比例的平均值为中心。这就是现在的工作。

于 2020-01-20T12:36:50.757 回答