Question: Two channel data vs. one colour data for PCA, heatmaps and clustering
0
7.7 years ago by
Maciej Jończyk720 wrote:
Dear John, I suppose that for the two-colour experiment you have also "A" (average expression) values. I don't know what package you have used but limma has RG.MA function which transforms MA data to RG (i.e. unlogged intensities). So you could construct MAlist object from your data, transform it to RGlist, (maybe take a log2) and you will have data for both channels. HTH, Maciej Jo?czyk > Dear Bioconductor. > In the past I have produced some PCA plots and heatmaps using one > colour data. On the PCA, it is useful to separate out the different > sample groups using the normalised expression values (say normal > coloured green and treatment coloured red). > > However, this sort of analyses does not seem possible with two colour > as you have a sinlge log2 normalised ratio (M value) as input to PCA > and heatmap functions. > > Does anyone have experience of doing PCA and/or heatmaps with 2 > colour > data? Any info/advice appreciated. > > John. -- Maciej Jonczyk, Department of Plant Molecular Ecophysiology Faculty of Biology, University of Warsaw 02-096 Warsaw, Miecznikowa 1 Poland -- This email was Anti Virus checked by Astaro Security Gateway. http://www.astaro.com
limma • 845 views
modified 7.7 years ago by Mayer, Claus-Dieter120 • written 7.7 years ago by Maciej Jończyk720
Answer: Two channel data vs. one colour data for PCA, heatmaps and clustering
0
7.7 years ago by
Samuel Wuest330
Samuel Wuest330 wrote:
Hi John, I would also recommend using the limma package for your type of analysis. After appropriate normalizations/bg-corrections, you can extract log-intensities from an MAList object using the exprs.MA() function. This will return a matrix object that you can use for pca/heatmaps as you've used before. It s possible that you have to relabel the columns and rows of the matrix accordingly (you probably want to use the info in the $targets and$genes slots of the MAList object, but there might be other ways to do that). The only drawback here is that correlations can occur between the two channels of an array, so for testing for differential gene expression in an unconnected design -after splitting the channels- I would refer to Chapter 9 of the limma user guide (see: limmaUsersGuide() ). Cheers, Sam ----------------------------------------------------- Samuel Wuest Smurfit Institute of Genetics Trinity College Dublin Dublin 2, Ireland Phone: +353-1-896 2444 Web: http://www.tcd.ie/Genetics/wellmer-2/index.html Email: wuests at tcd.ie ------------------------------------------------------ On 14 November 2011 10:52, mjonczyk <mjonczyk at="" biol.uw.edu.pl=""> wrote: > Dear John, > > I suppose that for the two-colour experiment you have also "A" (average > expression) values. > I don't know what package you have used but limma has RG.MA function > which transforms MA data to RG (i.e. unlogged intensities). > So you could construct MAlist object from your data, transform it to RGlist, > (maybe take a log2) and you will have data for both channels. > > HTH, > Maciej Jo?czyk > >> Dear Bioconductor. >> In the past I have produced some PCA plots and heatmaps using one >> colour data. On the PCA, it is useful to separate out the different >> sample groups using the normalised expression values (say normal >> coloured green and treatment coloured red). >> >> However, this sort of analyses does not seem possible with two colour >> as you have a sinlge log2 normalised ratio (M value) as input to PCA >> and heatmap functions. >> >> Does anyone have experience of doing PCA and/or heatmaps with 2 colour >> data? Any info/advice appreciated. >> >> John. > > -- > Maciej Jonczyk, > Department of Plant Molecular Ecophysiology > Faculty of Biology, University of Warsaw > 02-096 Warsaw, Miecznikowa 1 > Poland > > > > -- > This email was Anti Virus checked by Astaro Security Gateway. > http://www.astaro.com > > _______________________________________________ > 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
Hi Maciej and Samuel, I have tried your options and they seem to work pretty good. I normalised global loess and converted back to log2(R and G), then did eyayes diff-exp as a one colour array. The results are not exactly the same as the straight two colour but similar enough for me to be confident in such an approach and to use for PCA/heatmaps. Thank you very much for your help. Kind regards, John. 2011/11/14 Samuel Wuest <wuests at="" tcd.ie="">: > Hi John, > > I would also recommend using the limma package for your type of > analysis. After appropriate normalizations/bg-corrections, you can > extract log-intensities from an MAList object using the exprs.MA() > function. This will return a matrix object that you can use for > pca/heatmaps as you've used before. It s possible that you have to > relabel the columns and rows of the matrix accordingly (you probably > want to use the info in the $targets ?and$genes slots of the MAList > object, but there might be other ways to do that). > The only drawback here is that correlations can occur between the two > channels of an array, so for testing for differential gene expression > in an unconnected design -after splitting the channels- I would refer > to Chapter 9 of the limma user guide (see: limmaUsersGuide() ). > > Cheers, Sam > > ----------------------------------------------------- > Samuel Wuest > Smurfit Institute of Genetics > Trinity College Dublin > Dublin 2, Ireland > Phone: +353-1-896 2444 > Web: http://www.tcd.ie/Genetics/wellmer-2/index.html > Email: wuests at tcd.ie > ------------------------------------------------------ > > On 14 November 2011 10:52, mjonczyk <mjonczyk at="" biol.uw.edu.pl=""> wrote: >> Dear John, >> >> I suppose that for the two-colour experiment you have also "A" (average >> expression) values. >> I don't know what package you have used but limma has RG.MA function >> which transforms MA data to RG (i.e. unlogged intensities). >> So you could construct MAlist object from your data, transform it to RGlist, >> (maybe take a log2) and you will have data for both channels. >> >> HTH, >> Maciej Jo?czyk >> >>> Dear Bioconductor. >>> In the past I have produced some PCA plots and heatmaps using one >>> colour data. On the PCA, it is useful to separate out the different >>> sample groups using the normalised expression values (say normal >>> coloured green and treatment coloured red). >>> >>> However, this sort of analyses does not seem possible with two colour >>> as you have a sinlge log2 normalised ratio (M value) as input to PCA >>> and heatmap functions. >>> >>> Does anyone have experience of doing PCA and/or heatmaps with 2 colour >>> data? Any info/advice appreciated. >>> >>> John. >> >> -- >> Maciej Jonczyk, >> Department of Plant Molecular Ecophysiology >> Faculty of Biology, University of Warsaw >> 02-096 Warsaw, Miecznikowa 1 >> Poland >> >> >> >> -- >> This email was Anti Virus checked by Astaro Security Gateway. >> http://www.astaro.com >> >> _______________________________________________ >> 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 >
Answer: Two channel data vs. one colour data for PCA, heatmaps and clustering
0
7.7 years ago by
Mayer, Claus-Dieter120 wrote:
Hello, One issue I found with using the single channels of a two-colour experiment in a multivariate visualisation technique (PCA plots, clustering, heatmap, etc) is that array or dye effects can mask the sources of variation you are mostly interested in. Strong array effects mean that the two channels from the same array cluster together, strong dye effects can result in the red and green channels forming two big groups (normalisation can only eliminate these effects to a certain extent). In a PCA (or similar ordination method) it thus often makes sense to look at higher components (not only the first two). Best Wishes Claus Dr. Claus-D. Mayer Biomathematics & Statistics Scotland (BioSS) Rowett Institute of Nutrition and Health University of Aberdeen Aberdeen AB21 9SB, Scotland, UK. email: claus at bioss.ac.uk or c.mayer at abdn.ac.uk Telephone: +44 (0) 1224 716652 Biomathematics and Statistics Scotland (BioSS) is formally part of The James Hutton Institute, a registered Scottish charity No. SC041796 and a company limited by guarantee No. SC374831 > -----Original Message----- > From: bioconductor-bounces at r-project.org [mailto:bioconductor- > bounces at r-project.org] On Behalf Of mjonczyk > Sent: 14 November 2011 10:52 > To: arraystruggles at gmail.com; bioconductor at r-project.org > Subject: Re: [BioC] Two channel data vs. one colour data for PCA, > heatmaps and clustering > > Dear John, > > I suppose that for the two-colour experiment you have also "A" (average > expression) values. > I don't know what package you have used but limma has RG.MA function > which transforms MA data to RG (i.e. unlogged intensities). > So you could construct MAlist object from your data, transform it to > RGlist, > (maybe take a log2) and you will have data for both channels. > > HTH, > Maciej Jo?czyk > > > Dear Bioconductor. > > In the past I have produced some PCA plots and heatmaps using one > > colour data. On the PCA, it is useful to separate out the different > > sample groups using the normalised expression values (say normal > > coloured green and treatment coloured red). > > > > However, this sort of analyses does not seem possible with two colour > > as you have a sinlge log2 normalised ratio (M value) as input to PCA > > and heatmap functions. > > > > Does anyone have experience of doing PCA and/or heatmaps with 2 > > colour > > data? Any info/advice appreciated. > > > > John. > > -- > Maciej Jonczyk, > Department of Plant Molecular Ecophysiology > Faculty of Biology, University of Warsaw > 02-096 Warsaw, Miecznikowa 1 > Poland > > > > -- > This email was Anti Virus checked by Astaro Security Gateway. > http://www.astaro.com > > _______________________________________________ > 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 The University of Aberdeen is a charity registered in Scotland, No SC013683.