[BioC] some questions about lumi package and Illumina arrays

Wei Shi shi at wehi.EDU.AU
Fri Mar 30 00:18:35 CEST 2012

Dear Javier,

Firstly, let me point out that limma has its own pipeline for analyzing Illumina BeadChip data, which includes data input, neqc normalization, differential expression analysis, etc.. Section 11.7 in limma user's guide gives a case study for analyzing BeadChip data. The analysis included was performed at probe level.

We always perform probe level expression analysis for Illumina arrays. If you want to perform gene level analysis, you'll have to summarize probes to genes in some way. However, different probes for the same gene might have variable expression levels, due to multiple isoforms and other factors. This makes it hard to summarize probes and doing so may result in misleading results.  

On the other hand, you can choose a representative probe for each gene after you perform the probe level analysis, by choosing the one which has the largest average expression value across all samples for example. This will give you one expression value for each gene in each sample, if this is what you want.


On Mar 30, 2012, at 3:39 AM, Javier Pérez Florido wrote:

> Dear list,
> I have few questions about lumi package:
>  * How can the control plots be interpreted? For example:
>    plotControlData, plotHousekeepingGene and plotStringencyGene. I
>    don't know what the scenario to detect bad samples should be when
>    using these plots.
>  * What is the meaning of the density plot of coefficient of variance?
>    How can bad arrays be detected? Similar to traditional density plots
>    (that is, different distributions)?
>  * In lumi vignette, as well as in other packages, it is recommended to
>    work with probe information instead of gene information. For
>    example, when the sample probe profile file is opened, there might
>    be several probes that target the same gene. If working with such
>    sample probe profile file and after variance stabilizing transform
>    and normalization are made, the expression set generated can be used
>    as the input of limma. My question is: does limma detect
>    differentially expressed probes or differentially expressed genes?
>     From a practical point of view, is it the same?
> Thanks,
> Javier
> 	[[alternative HTML version deleted]]
> _______________________________________________
> Bioconductor mailing list
> Bioconductor at r-project.org
> https://stat.ethz.ch/mailman/listinfo/bioconductor
> Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor

The information in this email is confidential and intend...{{dropped:6}}

More information about the Bioconductor mailing list