如何获得pvalues列表？

Question

我执行了wilcox测试，现在我想将p.value提取到列表或矩阵中。

DF <- data.frame(A1=sample(1:9, 10, T), 
        A2=sample(1:9, 10, T), 
        A3=sample(1:9, 10, T), 
        B1=sample(1:9, 10, T), 
        B2=sample(1:9, 10, T), 
        B3=sample(1:9, 10, T)) 


sampA <- DF[,grep('A', names(DF))] # Sample with columns A 
sampB <- DF[,grep('B', names(DF))] # Sample with columns B 


lapply(1:nrow(DF), function(i){ 
    wilcox.test(as.numeric(sampA[i,]), as.numeric(sampB[i,]), exact=FALSE) 
}) 

我威尔科克斯测试的结果为每个行看起来是这样的： 我想知道我可以得到一个列表或矩阵的p.value导出到excel文件？ [[1]]

Wilcoxon rank sum test with continuity correction 

data: as.numeric(sampA[i, ]) and as.numeric(sampB[i, ]) 
W = 3, p-value = 0.6579 
alternative hypothesis: true location shift is not equal to 0 


[[2]] 

    Wilcoxon rank sum test with continuity correction 

data: as.numeric(sampA[i, ]) and as.numeric(sampB[i, ]) 
W = 0, p-value = 0.0722 
alternative hypothesis: true location shift is not equal to 0 


[[3]] 

    Wilcoxon rank sum test with continuity correction 

data: as.numeric(sampA[i, ]) and as.numeric(sampB[i, ]) 
W = 6, p-value = 0.6579 
alternative hypothesis: true location shift is not equal to 0 

Answer 1

只需添加$p.value从您wilcox.test对象中提取您的p.value：

lapply(1:nrow(DF), function(i){ 
    wilcox.test(as.numeric(sampA[i,]), as.numeric(sampB[i,]), exact=FALSE)$p.value 
}) 

其中给出：

[[1]] 
[1] 1 

[[2]] 
[1] 1 

[[3]] 
[1] 0.8247781 

[[4]] 
[1] 0.8247781 

通过使用sapply代替lapply你会得到一个向量而不是一个列表，这可能更容易操作。

sapply(1:nrow(DF), function(i){ 
    wilcox.test(as.numeric(sampA[i,]), as.numeric(sampB[i,]), exact=FALSE)$p.value 
}) 

# [1] 1.0000000 1.0000000 0.8247781 0.8247781 0.0765225 0.8247781 1.0000000 
# [8] 0.8247781 0.2682859 0.0765225 

Answer 2

使用sapply并引用p.value名称...

sapply(1:nrow(DF), function(i){wilcox.test(as.numeric(sampA[i,]), as.numeric(sampB[i,]), exact=FALSE)$p.value}) 

#[1] 0.8247781 0.0765225 0.8247781 1.0000000 0.2682859 0.6625206 1.0000000 
#[8] 0.1211833 0.5065552 0.8247781 

这将返回一个载体，而不是一个列表（我经常发现矢量更容易处理，比如因为你可以使用mylist[[1:5]]索引列表，但你可以做myvector[1:5]，但这是个人喜好