创建一个热图,其中数据中包含NaN值
我正在尝试使用该heatmap.2包创建热图.我的数据中有很多NaN值,我想做的是以下内容.每次有NaN值时,只需将单元格颜色设置为浅灰色(或其他一些中性颜色,可能是白色),然后将所有其他值(即log2表达式)设置为标准绿色/黄色/红色着色方案.这是我使用的代码:
heatmap.2(as.matrix(foo2[rowSums (abs(foo2)) != 0,]),
col = redgreen,
margins = c(12, 22),
trace = "none",
xlab = "Comparison",
lhei = c(2, 8),
scale = c("none"),
symbreaks = min(foo2 = 0, na.rm = TRUE),
na.color = "blue",
cexRow = 0.5,
cexCol = .7,
main = "DE geness",
Colv = F)
当没有NaN值时NaN,这很有效,但是当数据有时,我收到的错误是:
Error in hclustfun(distfun(x)) :
NA/NaN/Inf in foreign function call (arg 11)
从本质上讲,我想让它忽略NaN数据中的's'.我不知道如何处理这个问题.任何帮助将不胜感激.
pos*_*def 11
TL; DR:问题可能是委托distfun而非heatmap2功能本身.默认dist函数尝试计算数据点之间的距离,如果距离计算返回NA,则聚类函数无法处理.
版本较长:
我最近遇到了与OP相同的问题,并且不得不深入研究为什么问题不能为其他人重现.
基本问题如下:默认情况下hclust,heatmap2传递hclustfun和dist作为distfun参数.错误消息清楚地表明它不喜欢s hclustfun(在这种情况下默认为hclust)NA.
下一部分信息是这样的:即使数据矩阵包含NAs,dist(传入的hclust)结果也可能没有NA,这是@ kdauria答案的情况.见下文:
> library(gplots)
> mat = matrix( rnorm(25), 5, 5)
> mat[c(1,6,8,11,15,20,22,24)] = NaN
>
> heatmap.2( mat,
+ col = colorpanel(100,"red","yellow","green"),
+ margins = c(12, 22),
+ trace = "none",
+ xlab = "Comparison",
+ lhei = c(2, 8),
+ scale = c("none"),
+ symbreaks = min(mat, na.rm=TRUE),
+ na.color="blue",
+ cexRow = 0.5, cexCol = 0.7,
+ main = "DE genes",
+ dendrogram = "row",
+ Colv = FALSE )
> ?dist
> mat
[,1] [,2] [,3] [,4] [,5]
[1,] NaN NaN NaN -1.10103187 -1.4396185
[2,] -0.8821449 1.4891180 0.41956063 -0.06442867 NaN
[3,] -2.5912928 NaN -0.56603029 -0.55177559 -2.0313602
[4,] 0.8348197 0.2199583 0.06318663 1.59697764 NaN
[5,] -0.2632078 -1.2193110 NaN NaN 0.8618543
> dist(mat)
1 2 3 4
2 2.317915
3 1.276559 2.623637
4 6.032933 3.050821 5.283828
5 5.146250 4.392798 5.871684 2.862324
随机值矩阵不能重现问题,因为它避免了手头的问题.这让我想到了这样一个问题:从纳入NAs需要什么dist？
我的数据有一些偏大的值,我认为是原因,但我只是通过添加一行NA来重现问题:
> mat = matrix(rnorm(49), 7, 7)
> mat[c(3,17,28, 41)] = mat[c(3,17,28, 41)] * 100000
> mat
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -6.175928e-01 1.68691561 -1.233250e+00 -7.355322e-01 -0.37392178 3.559804e-01 1.7536137
[2,] 6.680429e-01 0.90590237 -1.375424e+00 5.842512e-01 -0.09376548 -3.556098e-01 -1.2926535
[3,] -3.739372e+04 -1.74534887 -2.241643e+05 -2.209226e-01 -0.86769435 -4.590908e-01 1.6306854
[4,] -1.283405e+00 0.20698245 3.635557e-01 3.673208e-01 -0.12339047 1.119922e+00 0.4301094
[5,] -5.430687e-02 -0.75219479 2.609126e+00 -1.340564e-01 0.54016622 2.885021e-01 0.9237946
[6,] -8.395116e-01 0.03675002 2.455545e+00 4.432025e-02 -0.86194910 1.302758e+05 0.6062505
[7,] 1.817036e-01 -1.46137388 -1.853179e+00 -2.177306e+03 2.36763806 -2.273134e+00 1.2440088
> dist(mat)
1 2 3 4 5 6
2 3.726858e+00
3 2.272605e+05 2.272606e+05
4 2.966078e+00 3.537475e+00 2.272620e+05
5 4.787577e+00 5.039154e+00 2.272644e+05 3.016614e+00
6 1.302754e+05 1.302762e+05 2.619559e+05 1.302747e+05 1.302755e+05
7 2.176576e+03 2.177895e+03 2.272705e+05 2.177679e+03 2.177179e+03 1.302963e+05
> mat = rbind(mat[1:4, ], rep(NA,7), mat[5:6, ])
> mat
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -6.175928e-01 1.68691561 -1.233250e+00 -0.73553223 -0.37392178 3.559804e-01 1.7536137
[2,] 6.680429e-01 0.90590237 -1.375424e+00 0.58425125 -0.09376548 -3.556098e-01 -1.2926535
[3,] -3.739372e+04 -1.74534887 -2.241643e+05 -0.22092261 -0.86769435 -4.590908e-01 1.6306854
[4,] -1.283405e+00 0.20698245 3.635557e-01 0.36732078 -0.12339047 1.119922e+00 0.4301094
[5,] NA NA NA NA NA NA NA
[6,] -5.430687e-02 -0.75219479 2.609126e+00 -0.13405635 0.54016622 2.885021e-01 0.9237946
[7,] -8.395116e-01 0.03675002 2.455545e+00 0.04432025 -0.86194910 1.302758e+05 0.6062505
> dist(mat)
1 2 3 4 5 6
2 3.726858e+00
3 2.272605e+05 2.272606e+05
4 2.966078e+00 3.537475e+00 2.272620e+05
5 NA NA NA NA
6 4.787577e+00 5.039154e+00 2.272644e+05 3.016614e+00 NA
7 1.302754e+05 1.302762e+05 2.619559e+05 1.302747e+05 NA 1.302755e+05
> heatmap.2( mat,
+ col = colorpanel(100,"red","yellow","green"),
+ margins = c(12, 22),
+ trace = "none",
+ xlab = "Comparison",
+ lhei = c(2, 8),
+ scale = c("none"),
+ symbreaks = min(mat, na.rm=TRUE),
+ na.color="blue",
+ cexRow = 0.5, cexCol = 0.7,
+ main = "DE genes",
+ dendrogram = "row",
+ Colv = FALSE )
Error in hclustfun(distfun(x)) :
NA/NaN/Inf in foreign function call (arg 11)
然而,这种情况似乎并不特定于存在完全由NA组成的行的情况.例如:
> mat
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] NaN NaN NaN NaN NA -7.531027e-01 0.2238252
[2,] 3.210084e-01 -1.55702840 2.777516e-01 0.2176875 1.3310334 -9.621561e-01 NaN
[3,] 1.159837e+05 0.04480172 -1.649482e+04 NaN 2.4748122 8.446133e-01 -0.4240776
[4,] -8.584051e-01 NaN NaN 1.0557713 -1.0855826 -5.638023e-02 -0.3789979
[5,] NA NA -2.539003e-01 -0.4552776 0.3856384 NA NA
[6,] NaN 1.31986556 NaN -1.0393147 -1.9197183 -1.434064e+00 0.6334569
[7,] NaN -0.42180912 NaN -0.8023476 -0.8264077 4.471358e+04 0.5046408
> dist(mat)
1 2 3 4 5 6
2 5.531033e-01
3 3.225471e+00 1.386143e+05
4 1.723619e+00 3.913983e+00 1.534332e+05
5 NA 1.949799e+00 3.085851e+04 3.945524e+00
6 1.486699e+00 6.010961e+00 6.905415e+00 3.743585e+00 4.449179e+00
7 8.365286e+04 5.915178e+04 5.914939e+04 5.915058e+04 2.358664e+00 5.290752e+04
kda*_*ria -1
我无法重现该问题。下面的代码工作得很好。所有 NaN 值均显示为蓝色。
library(gplots)
mat = matrix( rnorm(25), 5, 5)
mat[c(1,6,8,11,15,20,22,24)] = NaN
heatmap.2( mat,
col = colorpanel(100,"red","yellow","green"),
margins = c(12, 22),
trace = "none",
xlab = "Comparison",
lhei = c(2, 8),
scale = c("none"),
symbreaks = min(mat, na.rm=TRUE),
na.color="blue",
cexRow = 0.5, cexCol = 0.7,
main = "DE genes",
dendrogram = "row",
Colv = FALSE )
- 此示例并未反映 OP 最有可能经历的情况，因为它没有复制“dist(mat)”包含“NA”的情况。请参阅下面我的回答 (2认同)