Dear list!

 

I have data frames with 2 columns of normalised microarray data (more that 10k rows, custom-made array) with the following layout (not real data):

 

ID        M

ID1      -4.60138

ID2      -3.28832

ID3      4.83560

ID4      6.45286

ID4      6.65235

ID4      6.38745

ID4      6.74514

ID5      4.43995

ID6      -1.78943

ID7      -4.00257

ID8      -4.46327

ID9      -3.13956

ID10    2.52233

ID11    -1.81214

ID11    -1.78625

ID11    -1.61214

ID11    -1.52354

 

ID is the oligo ID (spot-ID), M is the corresponding M-value.

 

Only one spot per block is present in replicates (4). Therefore I would like to use one of the following 2 options:

 

1. Average the M-values in rows that have the same ID and extract the data table with both columns.

2. or if the first option does not work: Extract the rows with unique ID (both columns) and remove the replicates. I tried using "unique" on ID column but I couldn't extend its use to more than one column in the data frame.

 

I used R 2.4.0 and limma package for normalisation.

 

 

Thank you in advance,

 

 

Matjaz

 

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Matjaz Hren

 

National Institute of Biology

Department of Plant Physiology and Biotechnology

SLOVENIA

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