Question: Missing values - metaArray, GeneMeta, RankProd, metahdep
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gravatar for Maciej Jończyk
7.8 years ago by
Maciej Jończyk720 wrote:
Dear List Members, I'd like to perform a metaanalysis for few (minimum three) datasets. Some of them are one channel (Affymetrix), some two-colour data. Obviously, when I join, say three studies I will have big dataset in which some data will be missing. Just because some probes will be present in two experiments and absent in third experiment. I'd prefer not to use *only* probes which are present on all arrays, but also this which are present on two arrays. My *question* is: which package (metaArray, GeneMeta, RankProd, metahdep) could handle metaanalysis with missing data - in tutorials/manuals it is not stated if missing data is allowed. Although metaArray cites MergeMaid package as a example software for merging data with non-overlapping genes. Second *question* which of the above package will best handle dataset from merged two-colour and affymetrix studies? I'd also be grateful for directions to additional tutorials, materials, etc. Best Regards, Maciej Jończyk Maciej Jończyk, MSc Department of Plant Molecular Ecophysiology Institute of Plant Experimental Biology Faculty of Biology, University of Warsaw 02-096 Warszawa, Miecznikowa 1
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ADD COMMENTlink modified 7.8 years ago • written 7.8 years ago by Maciej Jończyk720
Answer: Missing values - metaArray, GeneMeta, RankProd, metahdep
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gravatar for John Stevens
7.8 years ago by
John Stevens30
John Stevens30 wrote:
Hi Maciej, My metahdep package doesn't require all datasets to come from the same array version -- so while the package's tutorial vignette doesn't explicitly say anything about missing values, the example there does allow for missing values in this sense (some genes not represented in all datasets). As to your second question, if you're combining studies with fundamentally different platforms (Affy for some, two-color for others, for example), you'll need to be careful to define an effect size (or some measure of differential expression) that means the same thing on all platforms, and for which you can calculate a meaningful standard error. I think trans-platform cases like this lead to the appeal of alternative scale methods such as those in the metaArray package (which uses the 'probability of expression' or POE scale). Regards, John Stevens ________________________________________ From: bioconductor-bounces@r-project.org [bioconductor- bounces@r-project.org] on behalf of mjonczyk@biol.uw.edu.pl [mjonczyk@biol.uw.edu.pl] Sent: Tuesday, August 09, 2011 1:45 PM To: bioconductor at r-project.org Subject: [BioC] Missing values - metaArray, GeneMeta, RankProd, metahdep Dear List Members, I'd like to perform a metaanalysis for few (minimum three) datasets. Some of them are one channel (Affymetrix), some two-colour data. Obviously, when I join, say three studies I will have big dataset in which some data will be missing. Just because some probes will be present in two experiments and absent in third experiment. I'd prefer not to use *only* probes which are present on all arrays, but also this which are present on two arrays. My *question* is: which package (metaArray, GeneMeta, RankProd, metahdep) could handle metaanalysis with missing data - in tutorials/manuals it is not stated if missing data is allowed. Although metaArray cites MergeMaid package as a example software for merging data with non-overlapping genes. Second *question* which of the above package will best handle dataset from merged two-colour and affymetrix studies? I'd also be grateful for directions to additional tutorials, materials, etc. Best Regards, Maciej Jończyk Maciej Jończyk, MSc Department of Plant Molecular Ecophysiology Institute of Plant Experimental Biology Faculty of Biology, University of Warsaw 02-096 Warszawa, Miecznikowa 1 _______________________________________________ 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
ADD COMMENTlink written 7.8 years ago by John Stevens30
Answer: Missing values - metaArray, GeneMeta, RankProd, metahdep
0
gravatar for Maciej Jończyk
7.8 years ago by
Maciej Jończyk720 wrote:
Hi John, thanks for reply. I've performed a part of example analysis from metaArray, I haven't succeeded to perform analysis on a dataset from three partially overlapping experiments. Zscore function gave results only for the common part. If I found a way to transform various experiments to effect-size scale (probably with inverse-variance method as recommended in Ramasamy et al. 2008 - very useful article) or something similar I will try metahdep. Best Regards, Maciej Jończyk > Hi Maciej, > > My metahdep package doesn't require all datasets to come from the same array version -- so while the package's tutorial vignette doesn't explicitly say anything about missing values, the example there does allow for missing values in this sense (some genes not represented in all datasets). > > As to your second question, if you're combining studies with fundamentally different platforms (Affy for some, two-color for others, for example), you'll need to be careful to define an effect size (or some measure of differential expression) that means the same thing on all platforms, and for which you can calculate a meaningful standard error. I think trans-platform cases like this lead to the appeal of alternative scale methods such as those in the metaArray package (which uses the 'probability of expression' or POE scale). > > Regards, > > John Stevens > > > > ________________________________________ > From: bioconductor-bounces at r-project.org [bioconductor-bounces at r-project.org] on behalf of mjonczyk at biol.uw.edu.pl [mjonczyk at biol.uw.edu.pl] > Sent: Tuesday, August 09, 2011 1:45 PM > To: bioconductor at r-project.org > Subject: [BioC] Missing values - metaArray, GeneMeta, RankProd, metahdep > > Dear List Members, > > I'd like to perform a metaanalysis for few (minimum three) datasets. > Some of them are one channel (Affymetrix), some two-colour data. > Obviously, when I join, say three studies I will have big dataset in > which some data will be missing. Just because some probes will be present > in two experiments and absent in third experiment. I'd prefer not to > use *only* probes which are present on all arrays, but also this which > are present on two arrays. > > My *question* is: which package (metaArray, GeneMeta, RankProd, metahdep) > could handle metaanalysis with missing data - in tutorials/manuals it is > not stated if missing data is allowed. Although metaArray cites MergeMaid > package as a example software for merging data with non-overlapping genes. > > Second *question* which of the above package will best handle dataset > from merged two-colour and affymetrix studies? > > I'd also be grateful for directions to additional tutorials, materials, etc. > > Best Regards, > Maciej Jończyk > > Maciej Jończyk, MSc > Department of Plant Molecular Ecophysiology > Institute of Plant Experimental Biology > Faculty of Biology, University of Warsaw > 02-096 Warszawa, Miecznikowa 1
ADD COMMENTlink written 7.8 years ago by Maciej Jończyk720
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