[BioC] arrayQualityMetrics

audrey audrey at ebi.ac.uk
Tue Jul 15 13:23:38 CEST 2008

Hi Steve,

1) The absence of background intensity will not have any hidden effect 
on the report. The only plot of the report that would make use of the 
background intensity is the spatial distribution, to see spatial 
effects. If you have R, G, Rb and Gb, each of them will be represented 
(4 spatial plots per array) and if only R and G are available, only 2 
spatial plots will be represented per array. There is no processing 
within the arrayQualityMetrics function. If you want to subtract 
background or normalise your data, you need to do it before (using limma 
for instance).

2) The RIN column is not needed in the phenoData, it was just an 
example. Another example would be, if you have a factor of interest, 
like treatment/control you can define a column in your phenoData with 
this information and then, when you call arrayQualityMetrics you can set 
the argument intgroup (which stands for interesting group) equal to the 
name of the column containing the treatment/control information. This 
will draw a colour side bar to your heatmap.

3) There are some examples here: 
http://www.microarray-quality.org/quality_metrics.html But they are not 
especially good/bad reports. It is a good suggestion, I will try to find 
some to share online.


Audrey Kauffmann
Cambridge UK

Steve Taylor wrote:
> Hi,
> I am using arrayQualityMetrics and have a few questions.
> 1) When creating the NChannelSet I am using Bluefuse data (the AMPCH1 
> and AMPCH2 columns) which do not have background readings, so I am 
> reading it in like this
> assayData = with(RG, assayDataNew(R=R, G=G))
> This seems to be ok but I was wondering if this has any knock on 
> effects I should be aware of, either with processing or report 
> generation?
> 2)RNA Integrity Number (RIN)    
> This seems to be required for phenoData, which is required to create 
> the NChannelSet. If I don't have these values what should I do?
> 3)I like the fact there are descriptions of different QC methods in 
> the report. What would also be helpful is if there were some example 
> reports online to compare what good/bad reports look like. Are there 
> any available?
> Thanks for any help,
> Steve
> ------------------------------------------------------------------
> Weatherall Institute of Molecular Medicine/Sir William Dunn School
> Oxford University
> _______________________________________________
> Bioconductor mailing list
> Bioconductor at stat.math.ethz.ch
> https://stat.ethz.ch/mailman/listinfo/bioconductor
> Search the archives: 
> http://news.gmane.org/gmane.science.biology.informatics.conductor

Audrey Kauffmann
Cambridge UK

More information about the Bioconductor mailing list