[R] Howto Compute Pairwise Similarity/Correlation Matrix from aData Frame

[Dimitris Rizopoulos]

try this:

mat.data <- data.matrix(data)
cor(t(mat.data))


I hope it helps.

Best,
Dimitris

----
Dimitris Rizopoulos
Biostatistical Centre
School of Public Health
Catholic University of Leuven

Address: Kapucijnenvoer 35, Leuven, Belgium
Tel: +32/(0)16/336899
Fax: +32/(0)16/337015
Web: http://med.kuleuven.be/biostat/
     http://www.student.kuleuven.be/~m0390867/dimitris.htm


----- Original Message ----- 
From: "Gundala Viswanath" <gundalav at gmail.com>
To: <r-help at stat.math.ethz.ch>
Sent: Wednesday, June 18, 2008 8:55 AM
Subject: [R] Howto Compute Pairwise Similarity/Correlation Matrix from 
aData Frame


> Hi,
>
> I have the following 5 vectors. I wish to compute
> the pairwise Pearson Correlation matrix with this data.frame.
> Is there a compact way to do it?
>
> At the end I hope to create a heatmap out of this correlation 
> matrix.
>
> __BEGIN__
>> data <- read.table("mydata.txt")
>> print(data)
>          V1      V2      V3      V4      V5      V6      V7      V8 
> V9
> 1       42.3    53.2    76.4    78.8    83.6    91.3    92.2   105.8 
> 109.6
> 2        6.8     9.7    12.7    13.1    14.6    16.3    17.2    17.9 
> 18.1
> 3       10.6    21.5    34.4    38.2    38.8    50.0    60.7    64.0 
> 64.3
> 4      215.3   227.4   227.7   245.0   257.2   260.0   269.8   287.3 
> 340.2
> 5        4.1     4.2     4.6     6.4     6.8     6.9    16.9    17.6 
> 23.3
>
> __END__
>
> Currently I am stuck in constructing the very matrix itself from
> double loop.
>
> __BEGIN__
> data <- read.table("GDS596_part1.txt")
> nofrow <- nrow(data)
>
> for (rwx in 1:nofrow) {
>   print(data[rwx,])
>   for (rwy in 1:nofrow) {
>      print(data[rwy,])
>
>       thecor <- cor(data[rwx,],data[rwy.], method="pearson")
>       # not sure how to proceed from here.
>   }
>
> }
> __END__
>
> Please advice.
>
> - Gundala Viswanath
> Jakarta - Indonesia
>
> ______________________________________________
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> PLEASE do read the posting guide 
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> and provide commented, minimal, self-contained, reproducible code.
> 


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