[R] aggregating data

[Iain Gallagher]

Hi Max

Using plyr instead of rehsape:

library(plyr)

df <- data.frame(gene=c('A', 'A', 'E', 'A', 'F', 'F'), probe = c(1,2,3,4,5,6))

ddply(df, .(gene), function(df)length(df$gene))

  gene V1
1    A  3
2    E  1
3    F  2

best

iain

--- On Thu, 30/6/11, Max Mariasegaram <max.mariasegaram at qut.edu.au> wrote:

> From: Max Mariasegaram <max.mariasegaram at qut.edu.au>
> Subject: [R] aggregating data
> To: "r-help at r-project.org" <r-help at r-project.org>
> Date: Thursday, 30 June, 2011, 8:28
> Hi,
> 
> I am interested in using the cast function in R to perform
> some aggregation. I did once manage to get it working, but
> have now forgotten how I did this. So here is my dilemma. I
> have several thousands of probes (about 180,000)
> corresponding to each gene; what I'd like to do is obtain is
> a frequency count of the various occurrences of each probes
> for each gene.
> 
> The data would look something like this:
> 
> Gene     ProbeID     
>          Expression_Level
> A         
>    1           
>   0.34
> A         
>    2           
>   0.21
> E              3 
>             0.11
> A         
>    4           
>   0.21
> F              5 
>             0.56
> F              6 
>             0.87
> .
> .
> .
> (180000 data points)
> 
> In each case, the probeID is unique. The output I am
> looking for is something like this:
> 
> Gene     No.ofprobes   
>   Mean_expression
> A         
>    3           
>   0.25
> 
> Is there an easy way to do this using "cast" or "melt"?
> Ideally, I would also like to see the unique probes
> corresponding to each gene in the wide format.
> 
> Thanks in advance
> Max
> 
> Maxy Mariasegaram| Reserach Fellow | Australian Prostate
> Cancer Research Centre| Level 1, Building 33 | Princess
> Alexandra Hospital | 199 Ipswich Road, Brisbane QLD 4102
> Australia | t: 07 3176 3073| f: 07 3176 7440 | e: mariaseg at qut.edu.au
> 
> 
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