Re: [R] caculate correlation

[Jim Lemon]

Hi Elham,
It looks to me as though you are looking for matches in the name field
and then asking for all columns except the first (-1). If you only
have two columns in "coding.rpkm", and "name" is the first column, you
will get whatever is in the second column that has a match in the
"name" column. I suspect that whatever you are doing to whatever is in
the data frames is just returning names, and without knowing what the
data frames look like, nobody can tell you what is going wrong.

Jim


On Tue, Jan 31, 2017 at 10:31 PM, Elham -  wrote:
> thank you for replay dear Jim,
> actually I`m new in R and I asked the person that teach correlation to
> me,but I have problem in it.
> please guide me, I can not understand why notwithstanding I transpose data,
> I do not have number in coding.rpkm[grep("23.C",coding.rpkm$name),-1]  and
> there is gene name instead of number
>
>
> On Tuesday, January 31, 2017 12:20 PM, Jim Lemon 
> wrote:
>
>
> Hi Elham,
>
> On Tue, Jan 31, 2017 at 7:28 PM, Elham -  wrote:
>> 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?!
>>
> Not in the values you are extracting from the data frame. As you are
> aware, you can only perform the "cor" operation on numbers. As the
> value returned refers to the correlation of _pairs_ of values, the
> vectors of numbers should be the same length and there should be some
> meaningful relationship between those pairs. Are you just trying to
> correlate any old numbers because they are numbers?
>
>> and at the end of print there is this error :
>>
>> <0 rows> (or 0-length row.names)
>>
> This is probably not an error, just R telling you that something that
> was requested didn't have anything in it. Maybe one day we will find
> out what is in:
>
> coding.rpkm
> ncoding.rpkm
>
> and we can provide more informed advice.
>
>
> Jim
>
>

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Re: [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  
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 -  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 
> 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 -  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 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 
>> 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
>>  wrote:
>>> for calculating correlation between coding and noncoding,first I
>>> transposed data ,(rows become columns) so row is control 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")
>>>
>>>        [[alternative HTML version deleted]]
>>>
>>> __
>>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>> PLEASE do read the posting guide
>>> http://www.R-project.org/posting-guide.html
>>> and provide commented, minimal, self-contained, reproducible code.
>>
>>
>
>


   
[[alternative HTML version deleted]]

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Re: [R] caculate correlation

[Jim Lemon]

Hi Elham,

On Tue, Jan 31, 2017 at 7:28 PM, Elham -  wrote:
> 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?!
>
Not in the values you are extracting from the data frame. As you are
aware, you can only perform the "cor" operation on numbers. As the
value returned refers to the correlation of _pairs_ of values, the
vectors of numbers should be the same length and there should be some
meaningful relationship between those pairs. Are you just trying to
correlate any old numbers because they are numbers?

> and at the end of print there is this error :
>
> <0 rows> (or 0-length row.names)
>
This is probably not an error, just R telling you that something that
was requested didn't have anything in it. Maybe one day we will find
out what is in:

coding.rpkm
ncoding.rpkm

and we can provide more informed advice.

Jim

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Re: [R] caculate correlation

[Jim Lemon]

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 -  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 
> 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 -  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 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 
>> 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
>>  wrote:
>>> for calculating correlation between coding and noncoding,first I
>>> transposed data ,(rows become columns) so row is control 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")
>>>
>>>[[alternative HTML version deleted]]
>>>
>>> __
>>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>> PLEASE do read the posting guide
>>> http://www.R-project.org/posting-guide.html
>>> and provide commented, minimal, self-contained, reproducible code.
>>
>>
>
>

__
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and provide commented, minimal, self-contained, reproducible code.

Re: [R] caculate correlation

[Elham - via R-help]

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  
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 -  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 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 
> 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
>  wrote:
>> for calculating correlation between coding and noncoding,first I
>> transposed data ,(rows become columns) so row is control 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")
>>
>>        [[alternative HTML version deleted]]
>>
>> __
>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>
>


   
[[alternative HTML version deleted]]

__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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and provide commented, minimal, self-contained, reproducible code.

Re: [R] caculate correlation

[Jim Lemon]

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 -  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 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 
> 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
>  wrote:
>> for calculating correlation between coding and noncoding,first I
>> transposed data ,(rows become columns) so row is control 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")
>>
>>[[alternative HTML version deleted]]
>>
>> __
>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>
>

__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

Re: [R] caculate correlation

[Elham - via R-help]

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 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  
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
 wrote:
> for calculating correlation between coding and noncoding,first I transposed 
> data ,(rows become columns) so row is control 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")
>
>        [[alternative HTML version deleted]]
>
> __
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.

   
[[alternative HTML version deleted]]

__
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Re: [R] caculate correlation

[Jim Lemon]

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
 wrote:
> for calculating correlation between coding and noncoding,first I transposed 
> data ,(rows become columns) so row is control 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")
>
> [[alternative HTML version deleted]]
>
> __
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.

__
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[R] caculate correlation

[Elham - via R-help]

for calculating correlation between coding and noncoding,first I transposed 
data ,(rows become columns) so row is control 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")

[[alternative HTML version deleted]]

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