Question: Microarray analysis using RMA method using affy, limma
0
gravatar for neranjan007
16 months ago by
neranjan0070 wrote:

Dear users,

I am trying to do a micro-array analysis using CEL files for S. aures using R.

  • I have used the following libraries:
source("https://bioconductor.org/biocLite.R")
library("affy")
library("limma")
library("genefilter")
  • Then I loaded the pd.s.aureus data set using the above and included it using the 
library("pd.s.aureus")
  • Then using the RMA method I imported the data to eset variable. After that I tried to do a non-specific filtering using nsFilter
esetF <- nsFilter(eset, remove.dupEntrez = FALSE,
                  var.cutoff = 0.5) 

 

Once I do that it gives me the error 

Error: getAnnMap: package saureus not available

 

But I have loaded the  "pd.s.aureus" library as there is no annotation data set in the name of saureus. (https://bioconductor.org/packages/3.7/data/annotation/

Is there anything I am missing here ? Is there a way around this? 

 

Thank you very much and any suggestion is much appreciated

Neranjan

 

ADD COMMENTlink modified 16 months ago • written 16 months ago by neranjan0070
Answer: micro array analysis using RMA method Using affy, limma
2
gravatar for James W. MacDonald
16 months ago by
United States
James W. MacDonald50k wrote:

The pd.s.aureus package isn't what you need. The annotate package is looking for a package called saureus.db that it wants to use for nsFilter. I don't remember if we ever supplied that package, but we don't do so now, so you are probably better off using nsFilter without filtering on Entrez Gene IDs. You can download the annotation package from ThermoFisher and parse that to get the mappings of probeset ID to Entrez Gene ID and then just filter your ExpressionSet by hand, based on whether or not there is an Entrez Gene ID for a given probeset.

ADD COMMENTlink written 16 months ago by James W. MacDonald50k
Answer: micro array analysis using RMA method Using affy, limma
2
gravatar for Gordon Smyth
16 months ago by
Gordon Smyth37k
Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia
Gordon Smyth37k wrote:

Since you have mentioned the limma package, I will add that doing variance filtering with nsFilter (by var.cutoff or otherwise) will interfere with your downstream limma analysis. You don't necessarily need to filter at all but, if you do, filtering on mean log-intensity is simpler and better in this context.

ADD COMMENTlink modified 16 months ago • written 16 months ago by Gordon Smyth37k
Answer: Microarray analysis using RMA method using affy, limma
0
gravatar for neranjan007
16 months ago by
neranjan0070 wrote:

This my first time analyzing Micro array data, all comments are valuable to me. If you know any tutorial or pipeline that I should be following / or have more information please let me know as well.

Thanks

ADD COMMENTlink written 16 months ago by neranjan0070
1

Please don't use the Add your answer box unless you are actually adding an answer.

There is a workflow that covers the basics, and then there is the limma User's Guide, which is a comprehensive guide for fitting a model and making comparisons.

ADD REPLYlink written 16 months ago by James W. MacDonald50k
1

The workflow at F1000 may also be a good place to start.

ADD REPLYlink written 16 months ago by Guido Hooiveld2.5k
Answer: Microarray analysis using RMA method using affy, limma
0
gravatar for neranjan007
16 months ago by
neranjan0070 wrote:

The microarray I am analyzing was done in 2010 and used Affymetrix microarray version 2.0. According to the files, I downloaded the version 31 from the Affymetrix data base, a CSV file using the following link. (https://www.affymetrix.com/support/technical/byproduct.affx?product=saureus     , file name = S_aureus.na31.annot.csv )

Since it's not a .db file version, I am not sure how to proceed in annotating the probs. 

 

I have 6 samples alltogether , and 3 samples in each condition. And this is what i did so far to get the p-values;

library(oligo)
​rawData <-  read.celfiles(celfiles)
#RMA normalization
normData <- rma(rawData)

library(limma)
normData2 <- normData[, normData$group %in% c("Control", "Salt")]
# Creating a design matrix
design <- model.matrix(~ normData2$group)
fit <- lmFit(normData2, design)
fit <- eBayes(fit)

And I got the pvalues and the padj values But I am unable to annotate the genes?

Is it possible to point out how the annotate the genes of S. aures ? 

 

Thank you very much.

 

ADD COMMENTlink modified 16 months ago • written 16 months ago by neranjan0070
1

Affymetrix provide annotation, which you can download from here:

http://www.affymetrix.com/support/technical/byproduct.affx?product=saureus

ADD REPLYlink modified 16 months ago • written 16 months ago by Gordon Smyth37k
Answer: Microarray analysis using RMA method using affy, limma
0
gravatar for neranjan007
16 months ago by
neranjan0070 wrote:

Do I need to remove the spikes (= hybridsation control probes) before doing the analysis ?  

ADD COMMENTlink written 16 months ago by neranjan0070
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