[BioC] applicability of tilingArray package

Michael Palumbo palumbo at wadsworth.org
Fri Nov 7 20:41:24 CET 2008


thanks for your thoughts. i have to say i'm afraid i only sort of follow 
what you've said. in an effort to clarify, it sounds like you've said 
the methods in the tilingArray package probably aren't a good approach 
to do the segmentation given the data i have.

you've said TAS's approach to the segmentation might be good, but 
finding the best parameters might be difficult. you've also said that 
for (i) i could use the methods of David et al and Huber et al using MM 
probes. if i do that, i'll be left with two separate collections (wt and 
mut) of normalized data, which i'll then need to find (ii), ie, the 
differentially transcribed regions and then segment those results.

the confusing part for me is connecting what you've said about TAS to 
using the MM normalizing methods. i don't see how i could use the MM 
normalizing methods and get 2 data sets of expression levels and then 
use TAS to find the differentially transcribed data and segments. maybe 
you're suggestion one or the other, ie, stick with TAS to do it all, or 
use huber et al, MM for normalizing and then find some other method to 
find the differentially transcribed regions and segmentation?


Wolfgang Huber wrote:
> Hi Michael,
> there are two separate issues:
> (i) finding the transcribed regions, separately in each of the samples
> (wt, mut).
> (ii) finding the differentially transcribed regions.
> For (i), you could use an approach similar to that in the David et al.
> and Huber et al. papers. Since you don't have the DNA reference hybes,
> you could use the MM probes. This is described in Section 4.2 of the
> vignette
> http://www.bioconductor.org/packages/2.3/bioc/vignettes/tilingArray/inst/doc/assessNorm.pdf
> and as the benchmarks in Section 5 show, it is not quite as good, but
> still pretty good.
> Don't think of this in terms of "normalising" the mutant against the
> "wt" type, that doesn't make much sense.
> For (ii), if you want to segment e.g. a probe-wise (moderated)
> t-statistic, the piecewise constant model using in the tilingArray
> package is not useful. A running window approach (like in TAS) makes
> sense, the hard part is of course tuning its parameters.
> AfaIk, there are methods for (i) and (ii) separately, and to join /
> align them, the approaches are ad hoc. It would be nice if there were a
> clean method that does (i) and (ii) jointly - maybe someone else has
> insights in this?
> Best wishes
>  Wolfgang
> ------------------------------------------------------------------
> Wolfgang Huber  EBI/EMBL  Cambridge UK  http://www.ebi.ac.uk/huber
> 04/11/2008 16:42 Michael Palumbo scripsit
>> hello,
>> i have general questions regarding the applicability of the tilingArray
>> package to my problem/data. i've used bioconductor in the past, but by
>> no means am i an expert.
>> i have data from affy yeast tiling arrays - 3 mut and 3 wild type. i've
>> run affy's TAS program on the CEL files - as a two sample analysis, ie,
>> comparing wt to mut and viewed the results in IGB. my initial goal is to
>> segment the results as was done in David et al, PNAS 2006. it seems to
>> me there are fundamental differences in my data and the data of David et
>> al. e.g., the normalization step described in tilingArray doc uses DNA
>> hybridized to the chips as a reference - i don't have that, although i
>> do have the wt data. a colleague thought i might be able to use the wt
>> data in the normalization step, but that doesn't seem quite right to me.
>> it is also described that normalization can occur by MM probes - maybe i
>> can normalize the mut chip data w/ MM probes and completely ignore the
>> wt data? i realize that if i did that, the result would no longer be a
>> comparison of mut and wt and what i would 'see' would be different from
>> what i currently see in IGB of the two sample TAS analysis. this also
>> seems like it's not the best approach.
>> on the other hand, again, all i really want to do is segment the
>> two-sample analysis that i've done. is there anything wrong with using
>> the results of TAS's analysis? TAS does a normalization and has
>> bandwidth averaging - as a non-expert, these are convenient and seem
>> good to me.
>> thanks in advance for any and all responses/thoughts,
>> mike palumbo

Michael Palumbo					palumbo at wadsworth.org
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