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Deleting multiple rows from a data matrix based on exp value

Hi,

Thanks for the quick reply.
However, your suggestion doesn't solve the problem I'm afraid (i.e
dim(Matrix) still the same). What I want is to reduce the number of
rows (probesets) markedly based on their normalized intensity - thus
I've chosen a cut-off of 1.11

When I run your code (as well as mine listed in my previous mail) R
just give me a very long list (in two columns) with the probeset names
as well as the expression value in column 17 (I've 25 columns in total
in my data matrix).
I have tried to generate a small matrix (4 rows and 3 colums) to test
your code... when I type head(Matrix) it looks ok (now only 3 rows as
expected), but when I type dim(matrix) it still states 4 rows and 3
colums...?

NB: When I write 'exp value' I mean log transformed, background
corrected expression values derived from Affy chips (I used the
'justRMA' command to read my CEL files and compute an expression
measure)

Kind regards,
Peter
On Mon, Nov 21, 2011 at 05:09, Dennis Murphy <djmuser at gmail.com> wrote: