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removing Control probesets

Hello,

I have some CEL files and a CDF file for them, now how I can remove Control probesets (probesets with name started by AFFX) please? I mean how I can define these probesets to enter them in text file to be excluded without need to R?

gene r
• 3,984 views • link
updated by Ram Ram • written by zizigolu zizigolu

Hi Alexander and thanks a lot,

I am not familiar enough with R and I don't know the nature of codes and just copying and pasting them from tutorials...

I entered your codes like below:

> library(affy)
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following object is masked from 'package:stats':

    xtabs

The following objects are masked from 'package:base':

    anyDuplicated, append, as.data.frame, as.vector, cbind, colnames,
    do.call, duplicated, eval, evalq, Filter, Find, get, intersect,
    is.unsorted, lapply, Map, mapply, match, mget, order, paste, pmax,
    pmax.int, pmin, pmin.int, Position, rank, rbind, Reduce, rep.int,
    rownames, sapply, setdiff, sort, table, tapply, union, unique,
    unlist, unsplit

Loading required package: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

>
> data <- ReadAffy()
> exp <- rma(data)

Background correcting
Normalizing
Calculating Expression
> control <- grep("AFFX",rownames(exp))
> exp <- exp[-control,]
>

Now where is the resulted normalized text file please to use it in the later purpose please? I need a normalized text file

If the control probsets have removed now that I use these Cel files as a input in RMAExpress for more normalizing?

• 0 views • link
updated by Ram Ram • written by zizigolu zizigolu

You won't need to normalise the data again. You can get the normalised text file with

write.exprs(exp, file="output.txt", sep="\t")
• 0 views • link
updated by Ram Ram • written by Alexander Skates Alexander Skates

Thank you very much

• 0 views • link
updated by Ram Ram • written by zizigolu zizigolu

1 answer

Hi Sarah, CEL files are binary files, so they will not be readable in a text editor -- you will have to use R or Matlab. Is there any reason in particular you do not want to use R?

Once they are loaded into R, it shouldn't be too difficult to remove them; given all of them have the standardised format of starting with "AFFX", you can use grep:

# load the affy library
library(affy)

# read CEL files in your working directory and normalise them
data <- ReadAffy() 
exp <- rma(data)

# remove all probes starting with "AFFX"
control <- grep("AFFX",rownames(exp))
exp <- exp[-control,]
• 0 views • link
updated by Ram Ram • written by Alexander Skates Alexander Skates

Sorry Alexander, with which codes in above script I could perform these arrays median centering and set standard deviation to 1 per array please?

• 0 views • link
updated by Ram Ram • written by zizigolu zizigolu 
# exprs gives a data frame with expression levels
e <- exprs(exp)

# median centreing
e <- apply(e,1,function(x) x-median(x))

# set SD to 1 with scale function
e.scaled <- t(scale(t(e),center=FALSE))
• 0 views • link
updated by Ram Ram • written by Alexander Skates Alexander Skates

Thank you for your valuable help

• 0 views • link
updated by Ram Ram • written by zizigolu zizigolu

So sorry to disturb you, but may I know please from where I can get these codes because whenever I am using sporadic codes from different tutorials, I face error then I got frustrated to R

• 0 views • link
updated by Ram Ram • written by zizigolu zizigolu

I know the feeling, I only started learning R recently too. It really is an invaluable tool to know your way around, and I'd recommend spending some time familiarising yourself with data types and methods if possible. I don't have any one resource that I use, I tend to go to either the manual pages or just simply Google things. I cannot stress how much having an underlying understanding of the language helps when amalgamating bits and pieces of code from the web though.

There is an online course that's started recently that might be of interest to you if you are interested in learning R: https://www.coursera.org/course/rprog

• 0 views • link
updated by Ram Ram • written by Alexander Skates Alexander Skates

Thanks again

• 0 views • link
updated by Ram Ram • written by zizigolu zizigolu

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