[BioC] Missing Autocorrelation in Ringo

[Torsten Waldminghaus]

Hi,

thanks for the answer and sorry for not making it more clear. I get a plot but it suggests that there is no autocorrelation. This means the column at point "0" is at 1.0 as usual but at "100", "200",... there are only dots which vary a bit in their size. Now the results you were interested in:

> str(exAc)
Class 'autocor.result'  atomic [1:11]  1.00000 -0.00469 -0.00660  0.00538  0.00652 ...
  ..- attr(*, "chromosome")= chr "1"

> ls(annoObject)
[1] "1.end"    "1.index"  "1.start"  "1.unique"

> head(annoObject["1.start"])
[1]  68 154 189 294 365 440


I tried the function extractProbeAnno but it does actually not seem to be there. R did not find it and I did also not find a help entry for it:

> help(extractProbeAnno)
No documentation for 'extractProbeAnno' in specified packages and libraries:
you could try 'help.search("extractProbeAnno")'

However, I could use for example posToProbeAnno and find the corresponding help page?!

Here is the session info:

> sessionInfo()
R version 2.7.2 (2008-08-25) 
i386-pc-mingw32 

locale:
LC_COLLATE=Norwegian (Bokmål)_Norway.1252;LC_CTYPE=Norwegian (Bokmål)_Norway.1252;LC_MONETARY=Norwegian (Bokmål)_Norway.1252;LC_NUMERIC=C;LC_TIME=Norwegian (Bokmål)_Norway.1252

attached base packages:
[1] splines   tools     stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] Ringo_1.4.0          SparseM_0.78         RColorBrewer_1.0-2   vsn_3.6.0            affy_1.18.2         
 [6] preprocessCore_1.2.1 affyio_1.8.1         geneplotter_1.18.0   annotate_1.18.0      xtable_1.5-4        
[11] AnnotationDbi_1.2.2  RSQLite_0.7-1        DBI_0.2-4            lattice_0.17-13      genefilter_1.20.1   
[16] survival_2.34-1      Biobase_2.0.1        limma_2.14.7        

loaded via a namespace (and not attached):
[1] grid_2.7.2         KernSmooth_2.22-22

Beyond the problems with getting the autocorrelation I was wondering if there is a good way to judge the quality of Ringo peak detection or the probability of getting wrong hits or loosing some?

Thanks for any help,
Torsten



-----Original Message-----
From: bioconductor-bounces at stat.math.ethz.ch [mailto:bioconductor-bounces at stat.math.ethz.ch] On Behalf Of Joern Toedling
Sent: 30. juni 2009 13:12
To: Torsten Waldminghaus; bioconductor at stat.math.ethz.ch
Subject: Re: [BioC] Missing Autocorrelation in Ringo

Hello,

to clarify, do you mean that the plot does not show anything or that the plot
indicates that there is no correlation? Is there an error message or warning?
If so, what does it say?

Further questions that could help me to figure out what is going on.
What is the result of
str(exAc)
ls(annoObject)
head(annoObject["1.start"])

Note that if your Agilent ChIP-chip files follow their convention to encode
the probe position in a colum called "SystematicName" then you can also use
the function "extractProbeAnno" on the RGList to obtain a probeAnno object.

Last but not least, what is the output of sessionInfo()? Please always specify
that when posting a question on the Bioconductor mailing list so that we can
figure out if there might be problem with the package versions.

Best regards,
Joern0


On Mon, 29 Jun 2009 14:17:00 +0200, Torsten Waldminghaus wrote
> Dear all,
> 
> I started using the Ringo package to analyze ChIP on Chip data and tried
> to make a nice plot of my nice autocorrelation. However, the plot shows
> no autocorrelation of neighbouring probes. This is unlikely to be
> because of the bad data, because I see really nice peaks when I plot
> signals on the chromosomal position and it fits very well with published
> data. If anybody has a suggestion what could be wrong or how I could
> find out what's wrong I would be happy.
> 
> This is what I do in more detail:
> 
> > RG <- read.maimages(files,"agilent")#read in array data
> 
> I wrote an annotation file which looks like this ("POSITIONS" and
> "PROBE_ID" come from the RG file above):
> 
> > annotationFile[1:3,]
> 
>   CHROMOSOME PROBE_ID POSITION LENGTH
> 
> 1          1        2   218268     60
> 
> 2          1        3  2239049     60
> 
> 3          1        6  3448934     60
> 
> This I used to make a probeAnno object like this:
> 
> > annoObject<-posToProbeAnno (annotationFile)
> 
> Than I calculate autocorrelation:
> 
> > exAc<-autocor(RG,probeAnno=annoObject, chrom="1",lag.max=1000)
> 
> And plot:
> 
> > plot(exAc)
> 
> Thanks for any help,
> 
> Torsten

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