Suggestion for affycomp
1
0
Entering edit mode
@hinrich-gohlmann-845
Last seen 10.3 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 • 1.4k views
ADD COMMENT
0
Entering edit mode
@hinrich-gohlmann-845
Last seen 10.3 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-) > >
ADD COMMENT
0
Entering edit mode
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 >
ADD REPLY

Login before adding your answer.

Traffic: 717 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6