ss wrote:
It is:

> data <- read.table('E-TABM-1-processed-data-1342561271_log2_with_symbols.txt', row.names = NULL ,header=TRUE, fill=TRUE)
 > class(data[3])
[1] "data.frame"
 >


Oops, should have said  class(data[[3]]) and
is.numeric(data[[3]])

See ?Extract


And if I try to use as.matrix(read.table()), I got:

>data <-as.matrix(read.table('E-TABM-1-processed-data-1342561271_log2_with_symbols.txt',
+ row.names = NULL ,header=TRUE, fill=TRUE))
 > 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"
You see they are surrounded by "".

I don't see such if I just use >read.table


That is because matrices (objects of class 'matrix') are of homogeneous type. It changes everything to a character (including the numbers), which you certainly do NOT want.

You want a data.frame, I will provide an example of what I think you are after.

Try the following commands and see how they compare to your situation: these work for me.

test <- data.frame(x = factor(rep(c("A", "B"), each = 13)), y = rnorm(26), z = rnorm(26))

test

class(test)

is.numeric(test[[2]])

is.numeric(test[[3]])

rowMeans(test)

rowMeans(test[2:3])

> data <- read.table('E-TABM-1-processed-data-1342561271_log2_with_symbols.txt', row.names = NULL ,header=TRUE, fill=TRUE)
 > 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


Thanks,
      Allen



On Thu, Jun 12, 2008 at 7:34 PM, Erik Iverson <[EMAIL PROTECTED] <mailto:[EMAIL PROTECTED]>> wrote:



    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]
        <mailto:[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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