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.mariasega...@qut.edu.au> wrote:
> From: Max Mariasegaram <max.mariasega...@qut.edu.au>
> Subject: [R] aggregating data
> To: "r-help@r-project.org" <r-help@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: maria...@qut.edu.au
>
>
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>
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