Three-color microarray analysis
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@thomas-sandmann-4297
Last seen 9.6 years ago
Dear all, I have received data obtained using a three-color microarray platform, e.g. three samples were labeled with three different fluorophores and hybridized competitively to a single array. Would anyone be able to point out a useful package for the analysis of three-color hybridizations ? Thanks a lot, Thomas -- Thomas Sandmann, PhD CellNetworks - Cluster of Excellence and Division Signaling and Functional Genomics (B110) Deutsches Krebsforschungszentrum Im Neuenheimer Feld 580 D-69120 Heidelberg Germany Phone: +49 6221 42 1954 [[alternative HTML version deleted]]
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@wolfgang-huber-3550
Last seen 3 months ago
EMBL European Molecular Biology Laborat…
Hi Thomas the NchannelSet class in the Biobase package can store such data [1], some of the normalisation [2] and QC-assessment [3] methods that are available for one- and two-color arrays can be either used directly or with a little adaptation to such data, as can the linear model based analysis of limma (e.g. by treating n 3-color arrays like 3n 1-color arrays). To be more specific, I think you will need to reveal the biological question and the experimental design behind these data. Best wishes Wolfgang [1] Have a look at the vignette of the CCl4 package "From the Genepix data files to RGList to NChannelSet" for an example where such an object is constructed, which you will need to adapt to the particular file format your friend uses (you'll have to modify the read.images function or emulate it with calls to read.table). [2] vsn, quantiles, ... [3] boxplots, MA-plots, between-array distance heatmap, such as in the arrayQualityMetrics package Il Oct/15/10 11:08 AM, Thomas Sandmann ha scritto: > Dear all, > > I have received data obtained using a three-color microarray platform, > e.g. three samples were labeled with three different fluorophores and > hybridized competitively to a single array. Would anyone be able to > point out a useful package for the analysis of three-color hybridizations ? > > Thanks a lot, > Thomas >
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Dear Wolfgang, thanks a lot for your pointers to all the different packages. To give you a bit more information about the experiment: In this study, two factors are investigated: genotype and food. Three different treatments were performed: A) wt genotype + normal food B) wt genotype + supplemented food C) mutant genotype + supplemented food Treatment/Genotype wt (W) mutant (M) Normal food (N) x NA Supplemented food (S) x x (x = data available, NA = not available) Each treatment was performed in four biological replicates, giving rise to 3 x 4 = 12 RNA samples. These 12 samples were analyzed on four 3-color microarrays, competitively hybridizing one sample from each treatment (A,B,C) to one array. Two contrasts are of interest to the researchers: 1.) For the wt genotype: genes with differential expression between the two food supplements (N, S) 2.) For "Supplemented food" (S) : genes with differential expression between wt and mutant genotypes (W, M) As these two question each refer to a single factor (either genotype OR food), I could perform two separate analyses on the data e.g. by treating the arrays like standard two-color hybridizations and extracting only the two channels of interest each time. Of course, I would be grateful for any advice, thanks, Thomas Wolfgang Huber wrote: > Hi Thomas > > the NchannelSet class in the Biobase package can store such data [1], > some of the normalisation [2] and QC-assessment [3] methods that are > available for one- and two-color arrays can be either used directly or > with a little adaptation to such data, as can the linear model based > analysis of limma (e.g. by treating n 3-color arrays like 3n 1-color > arrays). > > To be more specific, I think you will need to reveal the biological > question and the experimental design behind these data. > > Best wishes > Wolfgang > > > [1] Have a look at the vignette of the CCl4 package "From the Genepix > data files to RGList to NChannelSet" for an example where such an > object is constructed, which you will need to adapt to the particular > file format your friend uses (you'll have to modify the read.images > function or emulate it with calls to read.table). > > [2] vsn, quantiles, ... > > [3] boxplots, MA-plots, between-array distance heatmap, such as in the > arrayQualityMetrics package > > > Il Oct/15/10 11:08 AM, Thomas Sandmann ha scritto: >> Dear all, >> >> I have received data obtained using a three-color microarray platform, >> e.g. three samples were labeled with three different fluorophores and >> hybridized competitively to a single array. Would anyone be able to >> point out a useful package for the analysis of three-color >> hybridizations ? >> >> Thanks a lot, >> Thomas > > _______________________________________________ > Bioconductor mailing list > Bioconductor@stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor [[alternative HTML version deleted]]
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Hi Tom Sing, Thank you, this sounds reasonable. I think the analysis is conceptually not different from that of 4 replicates of 3 one-color arrays. So, you could think of the measurement for each gene as a point in 3D space, and consider different projections (e.g. on the plane normal to the average vector (1,1,1)), perhaps like Fig. 7 in http://www-huber.embl.de/pub/pdf/hvhv.pdf Depending on how that plot looks, one could attempt to detect gene set enrichment in different areas (directions) of the plot, e.g. using Hotelling's t-statistic and the applyByCategory function in the Category package; or the polar angle. Hope this helps. Wolfgang PS - was a dye swap performed between the four biological replicates? If not, I'd expect to pay a substantial amount of attention to confounding of biological effects with dye-effects. Il Oct/17/10 7:02 PM, Thomas Sandmann ha scritto: > Dear Wolfgang, > > thanks a lot for your pointers to all the different packages. > To give you a bit more information about the experiment: > > In this study, two factors are investigated: genotype and food. > Three different treatments were performed: > > A) wt genotype + normal food > B) wt genotype + supplemented food > C) mutant genotype + supplemented food > > Treatment/Genotype wt (W) mutant (M) > Normal food (N) x NA > Supplemented food (S) x x > > > (x = data available, NA = not available) > > Each treatment was performed in four biological replicates, giving rise > to 3 x 4 = 12 RNA samples. > These 12 samples were analyzed on four 3-color microarrays, > competitively hybridizing one sample from each treatment (A,B,C) to one > array. > > Two contrasts are of interest to the researchers: > > 1.) For the wt genotype: genes with differential expression between the > two food supplements (N, S) > 2.) For "Supplemented food" (S) : genes with differential expression > between wt and mutant genotypes (W, M) > > As these two question each refer to a single factor (either genotype OR > food), I could perform two separate analyses on the data e.g. by > treating the arrays like standard two-color hybridizations and > extracting only the two channels of interest each time. > > Of course, I would be grateful for any advice, > thanks, > > Thomas > > Wolfgang Huber wrote: >> Hi Thomas >> >> the NchannelSet class in the Biobase package can store such data [1], >> some of the normalisation [2] and QC-assessment [3] methods that are >> available for one- and two-color arrays can be either used directly or >> with a little adaptation to such data, as can the linear model based >> analysis of limma (e.g. by treating n 3-color arrays like 3n 1-color >> arrays). >> >> To be more specific, I think you will need to reveal the biological >> question and the experimental design behind these data. >> >> Best wishes >> Wolfgang >> >> >> [1] Have a look at the vignette of the CCl4 package "From the Genepix >> data files to RGList to NChannelSet" for an example where such an >> object is constructed, which you will need to adapt to the particular >> file format your friend uses (you'll have to modify the read.images >> function or emulate it with calls to read.table). >> >> [2] vsn, quantiles, ... >> >> [3] boxplots, MA-plots, between-array distance heatmap, such as in the >> arrayQualityMetrics package >> >> >> Il Oct/15/10 11:08 AM, Thomas Sandmann ha scritto: >>> Dear all, >>> >>> I have received data obtained using a three-color microarray platform, >>> e.g. three samples were labeled with three different fluorophores and >>> hybridized competitively to a single array. Would anyone be able to >>> point out a useful package for the analysis of three-color >>> hybridizations ? >>> >>> Thanks a lot, >>> Thomas >> >> _______________________________________________ >> 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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