Question

Limma Elist subsetting

0

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arfranco ▴ 130

@arfranco-8341

Last seen 21 hours ago

European Union

I am running a microarray analysis using limma containing some spike-in controls that allowed me to know that I got a linear signal response with a data$E >= 2.3, where data is a EList class object (data is microarray data already substracted and normalized), and data$E contains the intensity signal

Then, I tried to subset the data

data <- data[data$E >= 2.3]

But I got an error

Error: Two subscripts required

However if I run

> head(data$E >= 2.3)
        A    B    C    D    E    F
[1,] TRUE TRUE TRUE TRUE TRUE TRUE
[2,] TRUE TRUE TRUE TRUE TRUE TRUE
[3,] TRUE TRUE TRUE TRUE TRUE TRUE
[4,] TRUE TRUE TRUE TRUE TRUE TRUE
[5,] TRUE TRUE TRUE TRUE TRUE TRUE
[6,] TRUE TRUE TRUE TRUE TRUE TRUE

Any clue on how can I subset the data ?

microarray limma subsetting • 1.3k views

ADD COMMENT • link 6.7 years ago arfranco ▴ 130

score 0 · Answer 1 · 2016-06-06

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Axel Klenk ▴ 990

@axel-klenk-3224

Last seen 15 hours ago

Switzerland

data$E >= 2.3

specifies the rows you want to select but you need to specify the columns as well. If you want all columns:

data[data$E >= 2.3, ]

notice the "," -- one-character error :-)

Cheers,

- axel

ADD COMMENT • link 6.7 years ago Axel Klenk ▴ 990

score 0 · Answer 2 · 2016-06-06

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arfranco ▴ 130

@arfranco-8341

Last seen 21 hours ago

European Union

I forgot to mention I tried that solution as well, but it is not working (is not subsetting)

subset <- data[data$E >= 2.3,]
Error in object[[a]][i, j, drop = FALSE] : 
  (subscript) logical subscript too long

ADD COMMENT • link 6.7 years ago arfranco ▴ 130

1

Entering edit mode

sorry for not checking my answer... data$E is a matrix and not a vector...

so, exactly what do you want to subset? only rows with all values >= 2.3, e.g.

data[apply(data$E, 1, function(x) all(x >= 2.3)), ]

should do that; and there is package genefilter for more complicated things.

ADD REPLY • link 6.7 years ago Axel Klenk ▴ 990

3

Entering edit mode

Or, more elegantly and quickly:

data[rowSums(data$E >= 2.3) == ncol(data$E),] # rows with all values >= 2.3
data[rowSums(data$E >= 2.3) > 0,] # rows with any value >= 2.3
data[rowSums(data$E >= 2.3) == 2,] # rows with exactly 2 values >= 2.3

... and so on, for any number of values that you'd like to be greater-than-or-equal-to 2.3 per row.

ADD REPLY • link 6.7 years ago Aaron Lun ★ 28k