checking multi-modalities in histograms
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@javier-perez-florido-3121
Last seen 6.0 years ago
Dear list, Histograms are usually used to check the quality of microarray experiments. If there are bi-modalities in a particular array, it is a candidate to exclude it from the experiment. It is easy to check bi-modalities or multi-modalities visually, but I would like to know if there is a way (using a statistical test or something) to check multi-modalities using the data returned by the hist function. For an Affybatch object, hist function returns the X and Y values, but that's all, it doesn't return the variables breaks, counts, etc as it is said in the help manual for hist. So, I have two questions: * Is there a test to check for multi-modalities in histograms? * Is there a way to know the cells and the number of values per cell used by hist to check for multi-modalities in a rudimentary way? Thanks again, Javier [[alternative HTML version deleted]]
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Kevin Coombes ▴ 430
@kevin-coombes-3935
Last seen 17 months ago
United States
The Mclust R package has one set of tools to do this. I would also advise you to take a look at the bimodality index that we defined in Wang J, Wen S, Symmans WF, Pusztai L, Coombes KR. The bimodality index: a criterion for discovering and ranking bimodal signatures from cancer gene expression profiling data. Cancer Inform. 2009 Aug 5;7:199-216. PMID: 19718451 along with the editorial Ertel A. Bimodal gene expression and biomarker discovery. Cancer Inform. 2010 Feb 4;9:11-4. PMID: 20234772 An R package (ClassDiscovery) that includes a function to compute the bimodality index can be obtained from http://bioinformatics.mdanderson.org/Software/OOMPA/ Best, Kevin Javier P?rez Florido wrote: > Dear list, > Histograms are usually used to check the quality of microarray > experiments. If there are bi-modalities in a particular array, it is a > candidate to exclude it from the experiment. It is easy to check > bi-modalities or multi-modalities visually, but I would like to know if > there is a way (using a statistical test or something) to check > multi-modalities using the data returned by the hist function. > > For an Affybatch object, hist function returns the X and Y values, but > that's all, it doesn't return the variables breaks, counts, etc as it is > said in the help manual for hist. So, I have two questions: > > * Is there a test to check for multi-modalities in histograms? > * Is there a way to know the cells and the number of values per cell > used by hist to check for multi-modalities in a rudimentary way? > > Thanks again, > Javier > > > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor >
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Thanks Kevin, I had a look at the Mclust package and I don't see any function that could help me on this, could you please be more precise? On the other hand, I also had a look at the bimodalIndex function in ClassDiscovery package and I don't know which parameter of the BI variable is interesting for me. Moreover, I would like to check for bi-modalities or multi-bimodalities on affybatch objects (the hist function uses affybatch objects), which, as far as I know, cannnot be handled by the bimodalIndex function. Any suggestions? Thanks, Javier On 29/03/2010 19:41, Kevin Coombes wrote: > The Mclust R package has one set of tools to do this. > > I would also advise you to take a look at the bimodality index that we > defined in > Wang J, Wen S, Symmans WF, Pusztai L, Coombes KR. > The bimodality index: a criterion for discovering and ranking > bimodal signatures from cancer gene expression profiling data. > Cancer Inform. 2009 Aug 5;7:199-216. PMID: 19718451 > along with the editorial > Ertel A. > Bimodal gene expression and biomarker discovery. > Cancer Inform. 2010 Feb 4;9:11-4. PMID: 20234772 > > An R package (ClassDiscovery) that includes a function to compute the > bimodality index can be obtained from > http://bioinformatics.mdanderson.org/Software/OOMPA/ > > Best, > Kevin > > Javier P?rez Florido wrote: >> Dear list, >> Histograms are usually used to check the quality of microarray >> experiments. If there are bi-modalities in a particular array, it is >> a candidate to exclude it from the experiment. It is easy to check >> bi-modalities or multi-modalities visually, but I would like to know >> if there is a way (using a statistical test or something) to check >> multi-modalities using the data returned by the hist function. >> >> For an Affybatch object, hist function returns the X and Y values, >> but that's all, it doesn't return the variables breaks, counts, etc >> as it is said in the help manual for hist. So, I have two questions: >> >> * Is there a test to check for multi-modalities in histograms? >> * Is there a way to know the cells and the number of values per cell >> used by hist to check for multi-modalities in a rudimentary way? >> >> Thanks again, >> Javier >> >> >> [[alternative HTML version deleted]] >> >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor at stat.math.ethz.ch >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: >> http://news.gmane.org/gmane.science.biology.informatics.conductor >
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@wolfgang-huber-3550
Last seen 3 months ago
EMBL European Molecular Biology Laborat…
Dear Javier note that the number of modes of a distribution - can depend on the normalisation (before or after log-transformation; or whether background correction was done and how) - is impossible to determine from a finite sample without further assumptions (essentially a smoothing bandwidth) Besides these (significant) practical difficulties, I am also doubtfulof the usefulness, in terms of sensitivity and specificity, of this criterion for array quality diagnostics. If you see two modes, they would most likely be associated with a covariate, such as row, column, spatial position on the array. Then, if you find that this co- variate is quality-relevant, then I would advise checking for significant effects of that covariate even on arrays where the distribution looks uni-modal. Best wishes Wolfgang Mar 29, 2010, alle ore 6:14 PM, Javier P?rez Florido > Dear list, > Histograms are usually used to check the quality of microarray > experiments. If there are bi-modalities in a particular array, it is a > candidate to exclude it from the experiment. It is easy to check > bi-modalities or multi-modalities visually, but I would like to know if > there is a way (using a statistical test or something) to check > multi-modalities using the data returned by the hist function. > > For an Affybatch object, hist function returns the X and Y values, but > that's all, it doesn't return the variables breaks, counts, etc as it is > said in the help manual for hist. So, I have two questions: > > * Is there a test to check for multi-modalities in histograms? > * Is there a way to know the cells and the number of values per cell > used by hist to check for multi-modalities in a rudimentary way? > > Thanks again, > Javier > > > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor
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Dear Wolfgang, Thanks for your reply. The data I am going to test for bi-modalities are raw data, without preprocessing. For this purpose I think it is ideal to use bimodalIndex function from ClassDiscovery package. It tests for bimodalities using the information-based BIC criterion. I know that there are more quality metrics such as boxplots, MA plots, NUSE, etc...The use of histograms is complementary to all of them and all I need is something that says that, maybe, a CEL file isn't good due to such bi-modalities, taking into account the rest of quality metrics. Thanks again, Javier On 30/03/2010 14:54, Wolfgang Huber wrote: > Dear Javier > > note that the number of modes of a distribution > - can depend on the normalisation (before or after log- transformation; or whether background correction was done and how) > - is impossible to determine from a finite sample without further assumptions (essentially a smoothing bandwidth) > > Besides these (significant) practical difficulties, I am also doubtfulof the usefulness, in terms of sensitivity and specificity, of this criterion for array quality diagnostics. If you see two modes, they would most likely be associated with a covariate, such as row, column, spatial position on the array. Then, if you find that this co- variate is quality-relevant, then I would advise checking for significant effects of that covariate even on arrays where the distribution looks uni-modal. > > Best wishes > Wolfgang > > Mar 29, 2010, alle ore 6:14 PM, Javier P?rez Florido > > >> Dear list, >> Histograms are usually used to check the quality of microarray >> experiments. If there are bi-modalities in a particular array, it is a >> candidate to exclude it from the experiment. It is easy to check >> bi-modalities or multi-modalities visually, but I would like to know if >> there is a way (using a statistical test or something) to check >> multi-modalities using the data returned by the hist function. >> >> For an Affybatch object, hist function returns the X and Y values, but >> that's all, it doesn't return the variables breaks, counts, etc as it is >> said in the help manual for hist. So, I have two questions: >> >> * Is there a test to check for multi-modalities in histograms? >> * Is there a way to know the cells and the number of values per cell >> used by hist to check for multi-modalities in a rudimentary way? >> >> Thanks again, >> Javier >> >> >> [[alternative HTML version deleted]] >> >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor at stat.math.ethz.ch >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor >> > >
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Raw? Log-transformed? It almost certainly matters. The underlying model used by bimodalIndex (and by Mclust) is that of a mixture of normal distributions. On the raw-linear scale of most microarrays, the distributions are skewed. (In fact, the usual RMA background correction model is to view the data as a mixture of normal background with exponential noise.) I would expect that fitting a mixture-of-normals model to this data would almost always conclude that it was (at least) bimodal, with the long exponential tail representing one of the modes. Kevin Javier P?rez Florido wrote: > Dear Wolfgang, > Thanks for your reply. > The data I am going to test for bi-modalities are raw data, without > preprocessing. For this purpose I think it is ideal to use > bimodalIndex function from ClassDiscovery package. It tests for > bimodalities using the information-based BIC criterion. > I know that there are more quality metrics such as boxplots, MA plots, > NUSE, etc...The use of histograms is complementary to all of them and > all I need is something that says that, maybe, a CEL file isn't good > due to such bi-modalities, taking into account the rest of quality > metrics. > > Thanks again, > Javier > > > > On 30/03/2010 14:54, Wolfgang Huber wrote: >> Dear Javier >> >> note that the number of modes of a distribution >> - can depend on the normalisation (before or after >> log-transformation; or whether background correction was done and how) >> - is impossible to determine from a finite sample without further >> assumptions (essentially a smoothing bandwidth) >> >> Besides these (significant) practical difficulties, I am also >> doubtfulof the usefulness, in terms of sensitivity and specificity, >> of this criterion for array quality diagnostics. If you see two >> modes, they would most likely be associated with a covariate, such as >> row, column, spatial position on the array. Then, if you find that >> this co-variate is quality-relevant, then I would advise checking for >> significant effects of that covariate even on arrays where the >> distribution looks uni-modal. >> >> Best wishes >> Wolfgang >> >> Mar 29, 2010, alle ore 6:14 PM, Javier P?rez Florido >> >> >>> Dear list, >>> Histograms are usually used to check the quality of microarray >>> experiments. If there are bi-modalities in a particular array, it is a >>> candidate to exclude it from the experiment. It is easy to check >>> bi-modalities or multi-modalities visually, but I would like to know if >>> there is a way (using a statistical test or something) to check >>> multi-modalities using the data returned by the hist function. >>> >>> For an Affybatch object, hist function returns the X and Y values, but >>> that's all, it doesn't return the variables breaks, counts, etc as >>> it is >>> said in the help manual for hist. So, I have two questions: >>> >>> * Is there a test to check for multi-modalities in histograms? >>> * Is there a way to know the cells and the number of values per >>> cell >>> used by hist to check for multi-modalities in a rudimentary way? >>> >>> Thanks again, >>> Javier >>> >>> >>> [[alternative HTML version deleted]] >>> >>> _______________________________________________ >>> Bioconductor mailing list >>> Bioconductor at stat.math.ethz.ch >>> https://stat.ethz.ch/mailman/listinfo/bioconductor >>> Search the archives: >>> http://news.gmane.org/gmane.science.biology.informatics.conductor >>> >> >> > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor
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