[BioC] Post-justRMA "quality control"

[Michael Barnes]

Thanks for the reply.  Is it possible to do similar opperations on my
data (get justRMA values) and look at them in a similar way to the
probelevel data?  I liked the Vignette and how it showed the plots for
the probelevel data, then used "normalize" and then looked at the plots
again.  Does normalize return probe level data again?  If not, do you
have a suggestion how I might accomplishe this?

The memory comment was simply to explain what had happened.  I was one
of those guided through the memeory issues which is why I chose justRMA
instead of "normalize" when that failed.



Michael Barnes, Ph.D.

>>> ririzarr at jhsph.edu 08/20/03 12:01PM >>>
be aware that ReadAffy gives you probe level data. justRMA gives you 
gene expression level data. i prefer doing QC on the probe level
becuase, 
for one, the spatial proprerties are preserved. 

regarding the memory 
problem there have been many posts on the list. look through the 
mail archive and/or look at the R Windows FAQ.


On Wed, 20 Aug 2003, Michael Barnes wrote:

> I am trying to follow the "Load Data" Vignette in the section
entitled
> "quality control through data exploration".  I am using R1.7.1 and
> updated Bioconductor Tuesday (yesterday) on a Windows XP machine.  I
> have 23 U133A chips that I am trying to examine.
> 
> As I followed the process I was able to do all the actions
(histogram,
> boxplot, RNA degradation plot) on my dataset. 
> > data<-ReadAffy()
> 
> > data
> AffyBatch object
> size of arrays=712x712 features (91097 kb)
> cdf=HG-U133A (22283 affyids)
> number of samples=23
> number of genes=22283
> annotation=hgu133a
> >
> 
> I then wanted to see what my data looked like following
normalization
> (similar to what is described from pg 23 on).  However, due to
memeory
> issues I could not run the example in a manner similar to that
> described
> 
> > normalized.data<-normalize(data[1:23])
> Error: cannot allocate vector of size 91091 Kb
> 
>  so  I ran justRMA
> 
> > normalized.data<-justRMA()
> Background correcting
> Normalizing
> Calculating Expression
> 
> > sampleNames(normalized.data)
>  [1] "1082_U133A.CEL"       "1083_HG_U133A.CEL"    "1085_U133A.CEL"  
 
>  
>  [4] "1087_U133A.CEL"       "109335_U133A.CEL"     "109338_U133A.CEL"
 
>  
>  [7] "109341_U133A.CEL"     "109404_HG_U133A.CEL"  "1095_U133A.CEL"  
 
>  
> [10] "110256_U133A.CEL"     "110259_U133A.CEL"    
> "110442_HG_U133A.CEL" 
> [13] "110443_HG_U133A.CEL"  "110444_HG_U133A.CEL" 
> "110445_HG_U133A.CEL" 
> [16] "1349_U133A.CEL"       "1460_U133A.CEL"      
> "7021.31_HG_U133A.CEL"
> [19] "7113.3_HG_U133A.CEL"  "7118.3_HG_U133A.CEL" 
> "7149.3_HG_U133A.CEL" 
> [22] "813.31_HG_U133A.CEL"  "F1089_U133A.CEL"     
> 
> > normalized.data
> Expression Set (exprSet) with 
>         22283 genes
>         23 samples
>                  phenoData object with 1 variables and 23 cases
>          varLabels
>                 sample: arbitrary numbering
> >
> 
> Now I can not get boxplot or histogram.  I have not tried RNA
> degradation plot.
> 
> > boxplot(normalized.data,col=c(2,2,3,3))
> Error in boxplot.default(normalized.data, col = c(2, 2, 3, 3)) : 
>         invalid first argument
> >
> 
> > hist(normalized.data[1:2])
> Error in hist.default(normalized.data[1:2]) : 
>         `x' must be numeric
> >
> 
> If Ihave created an incompatible objecct with justRMA, how do I
create
> the correct object type?  If not, what suggestions do you have.
> 
> Michael Barnes, Ph.D.
> 
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