[Bioc-devel] Multiple colData in SummarizedExperiment

On 06/17/2015 11:41 AM, davide risso wrote:

Dear list,

I'm creating an R package to store RNA-seq data of a somewhat large 
project
in which I'm involved.

One of the initial goals is to compare different pre-processing 
pipelines,
hence I have multiple expression matrices corresponding to the same 
samples.
The SummarizedExperiment class seems a good candidate, since I have
multiple expression matrices with the same rowData and colData 
information.

I have several sample-specific variables that I want to store with the
object, namely, experimental information (e.g., batch, date, 
experimental
condition, ...) and sample quality (e.g., proportion of aligned reads,
total duplicate reads, etc...).

Of course, I can always create one big data frame concatenating the two
(experimental info + sample quality), but it seems that both 
conceptually
and practically, it might be useful to have two separate data frames.
Since this seems somewhat a reasonably standard type of information that
one would want to carry on, I was wondering if it would be possible /
useful to allow the user to have multiple data.frames in the colData 
slot

Actually, colData() is a DataFrame, and a DataFrame column can contain 
a DataFrame. So after

  example(SummarizedExperiment)

we could make some faux sample quality data

  quality = DataFrame(x=1:6, y=6:1, row.names=colnames(se1))

add this as a column in the colData()

  colData(se1)$quality = quality

(or create the SummarizedExperiment from a similar DataFrame up-front) 
and manage our grouped data

colData(se1)

DataFrame with 6 rows and 2 columns
    Treatment     quality
  <character> <DataFrame>
A        ChIP    ########
B       Input    ########
C        ChIP    ########
D       Input    ########
E        ChIP    ########
F       Input    ########

colData(se1[,1:2])$quality

DataFrame with 2 rows and 2 columns
          x         y
  <integer> <integer>
A         1         6
B         2         5

I'm not sure that this is any less confusing to the end user than 
having to manage a DataFrameList(), but it does not require any new 
features.

Martin

of SummarizedExperiment.

Best,
Davide

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