[R] caculate correlation

[Elham -]

Hi Dear Jim,

I did it, both return a vector of name of the genes with different length,as I said before I have list of coding and noncoding so the length are not same.
where is number?!

and at the end of print there is this error :

<0 rows> (or 0-length row.names)
 

    On Tuesday, January 31, 2017 3:07 AM, Jim Lemon <drjimlemon at gmail.com> wrote:
 

 Hi Elham,
What I meant is to simply copy these two expressions into the R command line:

coding.rpkm[grep("23.C",coding.rpkm$name),-1]

ncoding.rpkm[grep("23.C",ncoding.rpkm$name),-1]

and see what comes out. If both return a vector of numbers of the same
length with no NA values, my guess was wrong. If there are NA values,
try adding the argument use=pairwise.complete.obs to the "cor"
statement.

Jim


On Tue, Jan 31, 2017 at 9:17 AM, Elham - <ed_isfahani at yahoo.com> wrote:
> this script automatically recognizes what is control among cod and lnc. Note
> that this script contains a piece of text that is "grep(".C",cod$name)".
> This text select - among all column names - those that contain ".C". in my
> files, I named C1, C2, C3, etc all columns that correspond to controls. In
> the same manner, I get controls among the lnc, with the text:
> "grep(".C",lnc$name)"
>
> I`m so sorry,maybe I do not understand you again.
>
>
> On Tuesday, January 31, 2017 1:27 AM, Jim Lemon <drjimlemon at gmail.com>
> wrote:
>
>
> Hi Elham,
> This is about the same as your first message. What I meant was, what
> do these two expressions return? Is whatever is returned suitable
> input for the "cor" function?
>
> coding.rpkm[grep("23.C",coding.rpkm$name),-1]
>
> ncoding.rpkm[grep("23.C",ncoding.rpkm$name),-1]
>
> Jim
>
>
> On Tue, Jan 31, 2017 at 8:45 AM, Elham - <ed_isfahani at yahoo.com> wrote:
>> I have 9 experiments control/treatment that I analysed coding and
>> lncoding,
>> after that I normalize expression value.as you know we have different
>> known
>> number of coding and non -coding genes,so for calculating correlation
>> first
>> I transposed data ,(rows become columns)so row is control&treatment and
>> columns are gene names.(so I have 2 matrix with same row and different
>> column).This information is enough?
>>
>>
>>
>>
>> On Tuesday, January 31, 2017 1:06 AM, Jim Lemon <drjimlemon at gmail.com>
>> wrote:
>>
>>
>> Hi Elham,
>> Without knowing much about what coding.rpkm and ncoding.rkpm look
>> like, it is difficult to say. Have you tried to subset these matrices
>> as you do in the "cor" function and see what is returned?
>>
>> Jim
>>
>> On Tue, Jan 31, 2017 at 6:40 AM, Elham - via R-help
>> <r-help at r-project.org> wrote:
>>> for calculating correlation between coding and noncoding,first I
>>> transposed data ,(rows become columns) so row is control&treatment and
>>> columns are gene names.(so I have 2 matrix with same row and different
>>> column),I use these function for calculating correlation but all of
>>> spearman
>>> correlation are NA,why?
>>>
>>>
>>>
>>>
>>> control.corr=cor(coding.rpkm[grep("23.C",coding.rpkm$name),-1],ncoding.rpkm[grep("23.C",ncoding.rpkm$name),-1],method=
>>> "spearman")
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>> tumor.corr=cor(coding.rpkm [grep("27.T", coding.rpkm $name),-1],
>>> ncoding.rpkm [grep("27.T", ncoding.rpkm $name),-1],method = "spearman")
>>>
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>>>
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>>
>>
>
>


   
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