[英]Error using t.test - not enough 'x' observations
I have data where methylation has been measured. 我有测量甲基化的数据。
The data: data.frame
, 900
observations x 70
patients [30 ctrl, 40 case], all values are numeric
, no NA
s. 数据:
data.frame
, 900
观察值x 70
患者[30 ctrl,40例],所有值均为numeric
,无NA
。
I use the following code: 我使用以下代码:
group <- function(dFrame,toMatch)
{
matches <- unique (grep(paste(toMatch,collapse="|"),
colnames(dFrame), value=TRUE))
return(dFrame[matches])
}
pValue <- sapply(methySample, function(x) t.test( group (x,'case'),group (x,'ctrl'))$p.value)
Error in t.test.default(group (x, "case"), group (x, "ctrl")) :
not enough 'x' observations
I want pValue to be a vector with one entry for each observation-row. 我希望pValue是一个向量,每个观察行都有一个条目。
EDIT2: Here is an example - shortened but you should get the idea: EDIT2:这是一个示例-简化了,但您应该明白这一点:
case_01 case_02 case_03 ctrl_01 ctrl_02 ...
1 0.876729 0.8760000 0.8835130 0.8999369 0.8642505
2 0.8270763 0.7983686 0.8092107 0.8610273 0.8475543
3 0.2591350 0.2829770 0.2735919 0.2556579 0.2735417
4 0.8181337 0.8007408 0.7808821 0.8097073 0.7511147
5 0.6217151 0.6061754 0.5850365 0.6151368 0.5680856
6 0.6943685 0.7605200 0.6855676 0.6687362 0.7320926
...
Maybe someone here can help me to figure out what went wrong - maybe I am missing something obvious here. 也许这里有人可以帮助我找出问题所在-也许我在这里遗漏了一些明显的东西。 I have already seen other posts considering this error message but the answers were like 'do you have NAs in your data?'
我已经看过其他有关此错误消息的帖子,但答案就像“您的数据中是否包含NA?”。 'oh yea!'
“哦,是的!” - this does not apply for my problem.. Thank you!
-这不适用于我的问题。。谢谢!
I'm going to go out on a limb and guess that you want to apply the the t-test for each row in your data.frame and the fields are labeled 'case1','control1', etc. 我会费力地想一下,您想对data.frame中的每一行应用t检验,并且字段标记为'case1','control1'等。
methySample <-
data.frame(case1=rnorm(10),
case2=rnorm(10),
control1=rnorm(10),
control2=rnorm(10))
# identify the fields that are labeled 'case' and 'control'
caseFields <- grep('case',colnames(methySample), value=TRUE)
controlFields <- grep('control',colnames(methySample), value=TRUE)
# apply the t-test for each row (margin = 1)
apply(methySample,
1,
function(x)
t.test(x[caseFields],
x[controlFields])$p.value)
If you're still having trouble, this bit of code is equivalent and probably easier to debug: 如果您仍然遇到问题,那么这段代码是等效的,并且可能更容易调试:
pValue <- numeric(0)
for(i in seq(nrow(methySample)))
pValue <- c(pValue,
t.test(methySample[i,caseFields],
methySample[i,controlFields])$p.value)
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