ss wrote:
Hi Wacek,
Yes, data is data frame not a matrix.
is.numeric(data[3])
[1] FALSE
what is class(data[3])
But I looked at the column 3 and it looks okay though. There are few NAs and
I did find
anything strange.
Any suggestions?
Thanks,
Allen
On Thu, Jun 12, 2008 at 7:01 PM, Wacek Kusnierczyk <
[EMAIL PROTECTED]> wrote:
ss wrote:
Thank you very much, Wacek! It works very well.
But there is a minor problem. I did the following:
data <-
read.table('E-TABM-1-processed-data-1342561271_log2_with_symbols.txt',
+row.names = NULL ,header=TRUE, fill=TRUE)
looks like you have a data frame, not a matrix
dim(data)
[1] 23963 85
data[1:4,1:4]
Probe_ID Gene_Symbol M16012391010920 M16012391010525
1 A_23_P105862 13CDNA73 -1.6 0.16
2 A_23_P76435 15E1.2 0.18 0.59
3 A_24_P402115 15E1.2 1.63 -0.62
4 A_32_P227764 15E1.2 -0.76 -0.42
data1<-data[sapply(data, is.numeric)]
dim(data1)
[1] 23963 82
data1[1:4,1:4]
M16012391010525 M16012391010843 M16012391010531 M16012391010921
1 0.16 -0.23 -1.40 0.90
2 0.59 0.28 -0.30 0.08
3 -0.62 -0.62 -0.22 -0.18
4 -0.42 0.01 0.28 -0.79
You will notice that, after using 'data[sapply(data, is.numeric)]' and
getting
data1, the first sample in data, called 'M16012391010920', was missed
in data1.
Any further suggestions?
surely there must be an entry in column 3 that makes it non-numeric.
what does is.numeric(data[3]) say? (NAs should not make a column
non-numeric, unless there are only NAs there, which is not the case
here.) check your data for non-numeric entries in column 3, there can
be a typo.
vQ
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