我有一个非常奇怪的问题，一个双打矩阵变成一个字符串矩阵。我将我的代码减少到以下问题：
num.samples <- nrow(expr.matrix)
num.genes <- ncol(expr.matrix)
gene.names <- colnames(expr.matrix)
# Define a function which returns a vector in order to...
execute.per.gene <- function(target.gene, ...) {
# Uninteresting code
x <- expr.matrix[,setdiff(1:num.genes, target.gene)]
y <- expr.matrix[,target.gene]
rf <- randomForest(x, y, mtry=10, ntree=100, importance=TRUE)
# Calculate importance measure
im <- importance(rf)[,"IncNodePurity"]
# Divide by number of samples
im / num.samples
}
# ... execute mclapply!
all.output <- mclapply(1:num.genes, execute.per.gene, mc.cores=mc.cores)
# Initialise matrix
weight.matrix <- matrix(0.0, nrow=num.genes, ncol=num.genes)
rownames(weight.matrix) <- gene.names
colnames(weight.matrix) <- gene.names
# And now I merge the results from 'all.output' into the weight.matrix
for (target.gene in 1:num.genes) {
# Get result
im <- all.output[[target.gene]]
# Find which rows to change for this column
cand.tf.idx <- match(names(im), gene.names)
# Merge results into output matrix
weight.matrix[cand.tf.idx, target.gene] <- im
}
# And suddenly, the matrix consists of a bunch of strings!
if (!is.numeric(weight.matrix[[1,1]])) { # dafuq
cat("\nEncountered strings! :/\n")
print(weight.matrix)
# recently added this for debugging purposes:
print(sapply(all.output, class))
browser()
}
输出结果为：
Encountered strings! :/
G1 G7 G9 G23 G26 G28 G29 G33 G44 G48 G50 G52 G55 G59 G63 G64 G69 G70
G1 "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0"
G7 "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0"
G9 "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0"
G23 "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0"
G26 "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0" "0"
...
我有没有线索为什么矩阵变成了一堆包含零的字符串。毕竟，在execute.per.gene方法中，我做的最后一件事是将向量除以整数，问题不会在那时引发异常，因此im必须仍然是向量那时加倍。
有人看到问题所在吗？我做错了什么？
更新，im应该总是看起来像下面这样。如果im已经包含字符串，我认为im / num.samples会失败。
> dput(im)
structure(c(3.86421872658217, 0.0600404651226161, 0.0729843866848986,
0.0556398483535666, 0.0488815568218319, 0.0526059937835038, 0.170688282373908,
0.129655447072086, 0.174050696716209, 0.244770969072866, 0.170282014024477,
0.100440545265572, 0.0634773436494396, 0.0696835665372604, 0.118303002740336,
0.0493612110879677, 0.103414668075989, 0.0149516634700066, 0.0377397612656266,
0.0462366818296757, 0.0534595079995701, 0.0418429987271517, 0.0521335103883387,
0.0454590053400778, 0.0620792864477719, 0.0528642019860386, 0.0440233200010488,
....
2.4293680818691, 0.0455845647048088, 0.0480473721971548, 0.0493418345253576,
0.0468391879447859, 1.53509517636789, 0.0639471582428624, 0.155340800410008,
0.0668494853135931, 0.0436381864919185, 1.09024170028797, 0.0649503734307499,
0.0490042073829033, 0.0304435411561372, 0.034892331733943, 0.0759421587532521,
0.0666974014679768, 0.913196971375135, 0.0550660353121449, 1.36191204205922,
3.63194611493454, 0.177078251458191, 0.17856008667256, 0.0499985787306069,
0.0465138307009715, 0.071656156183379, 0.0441178391009568, 0.239933902772204,
0.0719828575374175, 0.0654148345872996, 0.920668929212975, 0.0454979263784418,
2.92899170564573, 0.0208273505572265, 0.0397416566013167, 0.197310579354446,
0.0313568556466712), .Names = c("sample_2", "sample_3", "sample_4",
"sample_5", "sample_6", "sample_7", "sample_8", "sample_9", "sample_10",
"sample_11", "sample_12", "sample_13", "sample_14", "sample_15",
"sample_16", "sample_17", "sample_18", "sample_19", "sample_20",
"sample_21", "sample_22", "sample_23", "sample_24", "sample_25",
"sample_26", "sample_27", "sample_28", "sample_29", "sample_30",
"sample_31", "sample_32", "sample_33", "sample_34", "sample_35",
"sample_36", "sample_37", "sample_38", "sample_39", "sample_40",
"sample_41", "sample_42", "sample_43", "sample_44", "sample_45",
"sample_46", "sample_47", "sample_48", "sample_49", "sample_50",
"sample_51", "sample_52", "sample_53", "sample_54", "sample_55",
"sample_56", "sample_57", "sample_58", "sample_59", "sample_60",
"sample_61", "sample_62", "sample_63", "sample_64", "sample_65",
"sample_66", "sample_67", "sample_68", "sample_69", "sample_70",
"sample_71", "sample_72", "sample_73", "sample_74", "sample_75",
....
"sample_801", "sample_802", "sample_803", "sample_804", "sample_805"
))
有关gene.names，num.samples和num.genes的更多信息：
> dput(num.samples)
1643L
> dput(num.genes)
805L
> dput(gene.names)
c("sample_1", "sample_2", "sample_3", "sample_4", "sample_5",
"sample_6", "sample_7", "sample_8", "sample_9", "sample_10",
"sample_11", "sample_12", "sample_13", "sample_14", "sample_15",
"sample_16", "sample_17", "sample_18", "sample_19", "sample_20",
"sample_21", "sample_22", "sample_23", "sample_24", "sample_25",
"sample_26", "sample_27", "sample_28", "sample_29", "sample_30",
"sample_31", "sample_32", "sample_33", "sample_34", "sample_35",
"sample_36", "sample_37", "sample_38", "sample_39", "sample_40",
...
"sample_741", "sample_742", "sample_743", "sample_744", "sample_745",
"sample_746", "sample_747", "sample_748", "sample_749", "sample_750",
"sample_751", "sample_752", "sample_753", "sample_754", "sample_755",
"sample_756", "sample_757", "sample_758", "sample_759", "sample_760",
"sample_761", "sample_762", "sample_763", "sample_764", "sample_765",
"sample_766", "sample_767", "sample_768", "sample_769", "sample_770",
"sample_771", "sample_772", "sample_773", "sample_774", "sample_775",
"sample_776", "sample_777", "sample_778", "sample_779", "sample_780",
"sample_781", "sample_782", "sample_783", "sample_784", "sample_785",
"sample_786", "sample_787", "sample_788", "sample_789", "sample_790",
"sample_791", "sample_792", "sample_793", "sample_794", "sample_795",
"sample_796", "sample_797", "sample_798", "sample_799", "sample_800",
"sample_801", "sample_802", "sample_803", "sample_804", "sample_805"
)
答案 0 :(得分：0)
感谢所有帮助，我发现了问题:)
在一些非常不可能的条件下expr.matrix包含一些NaN值，randomForests算法会翻转。
browser()提示非常有用！