Suggestion for affycomp
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@hinrich-gohlmann-845
Last seen 10.2 years ago
Good morning, I have a suggestion for affycomp and it's accompanying web site at http://affycomp.biostat.jhsph.edu/AFFY2/TABLES.hgu/0.html I very much like the idea to check how the different algorithms perform but I would even more appreciate a biologist-compatible interpretation of the comparison table (low or no stats!). What I have in mind is something like: (1) define all the different approaches that people could be interested in from a statistical point of view (Example: I am interested in a best possible accuracy of fold change estimation at all signal levels. For this application, score components 4, 7, and 13 are most important (I don't know!). OR: I would like to have the highest possible precision for the signal levels. For this application score components 3, 6, 8, and 11 are most important. OR: I need best possible precision for low expressed genes. For this components x, y, and z are most important. And so on... (2) make a table with those applications and give the 2 or three best suitable algorithms for those applications. By openly defining those applications at such a web site, we can get a discussion going on what components most people agree on per application and can secondly make practical use of the data that gets collected. Cheers, hinrich d8-)
affycomp affycomp • 1.3k views
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@hinrich-gohlmann-845
Last seen 10.2 years ago
Hi, hmmm... was my question/suggestion that weird or not understandable (English is not my native language...) or is there simply no need for such an overview table? Cheers, hinrich d8-) Hinrich G?hlmann wrote: > Good morning, > > I have a suggestion for affycomp and it's accompanying web site at > http://affycomp.biostat.jhsph.edu/AFFY2/TABLES.hgu/0.html > > I very much like the idea to check how the different algorithms perform > but I would even more appreciate a biologist-compatible interpretation > of the comparison table (low or no stats!). What I have in mind is > something like: > (1) define all the different approaches that people could be interested > in from a statistical point of view (Example: I am interested in a best > possible accuracy of fold change estimation at all signal levels. For > this application, score components 4, 7, and 13 are most important (I > don't know!). OR: I would like to have the highest possible precision > for the signal levels. For this application score components 3, 6, 8, > and 11 are most important. OR: I need best possible precision for low > expressed genes. For this components x, y, and z are most important. And > so on... > (2) make a table with those applications and give the 2 or three best > suitable algorithms for those applications. > > By openly defining those applications at such a web site, we can get a > discussion going on what components most people agree on per application > and can secondly make practical use of the data that gets collected. > > Cheers, > hinrich d8-) > >
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apart from the legends given in the web-page, the paper describing affycomp it explains each measure in more detail. http://bioinformatics.oupjournals.org/cgi/content/abstract/20/3/323?ij key=83iw8rxPSScW6&keytype=ref a more biologist friendly explanation is possible but requires time which we dont necessarily have right now. contributions are welcomed. -r On Mon, 19 Jul 2004, [ISO-8859-1] Hinrich Göhlmann wrote: > Hi, > > hmmm... was my question/suggestion that weird or not understandable > (English is not my native language...) or is there simply no need for > such an overview table? > > Cheers, > hinrich d8-) > > > Hinrich Göhlmann wrote: > > Good morning, > > > > I have a suggestion for affycomp and it's accompanying web site at > > http://affycomp.biostat.jhsph.edu/AFFY2/TABLES.hgu/0.html > > > > I very much like the idea to check how the different algorithms perform > > but I would even more appreciate a biologist-compatible interpretation > > of the comparison table (low or no stats!). What I have in mind is > > something like: > > (1) define all the different approaches that people could be interested > > in from a statistical point of view (Example: I am interested in a best > > possible accuracy of fold change estimation at all signal levels. For > > this application, score components 4, 7, and 13 are most important (I > > don't know!). OR: I would like to have the highest possible precision > > for the signal levels. For this application score components 3, 6, 8, > > and 11 are most important. OR: I need best possible precision for low > > expressed genes. For this components x, y, and z are most important. And > > so on... > > (2) make a table with those applications and give the 2 or three best > > suitable algorithms for those applications. > > > > By openly defining those applications at such a web site, we can get a > > discussion going on what components most people agree on per application > > and can secondly make practical use of the data that gets collected. > > > > Cheers, > > hinrich d8-) > > > > > > _______________________________________________ > Bioconductor mailing list > Bioconductor@stat.math.ethz.ch > https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor >
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