how to do quantile normalization under dye swape situation
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@yanjuliacsnl-1786
Last seen 10.2 years ago
Hello All, my microarray datasets are like follows. And I want to normalize the data. Targets: Sample FileName Dye Stage Cy3 Cy5 ZWS57 57.gpr T5C3 high oblong ref high ZWS58 58.gpr T3C5 high oblong high ref ZWS61 61.gpr T5C3 high oblong ref high ZWS62 62.gpr T3C5 high oblong high ref ref is the commen reference. First I think Within Array Normalization is not neccesary (am i right?). Then I want to do the Between Array Normalization using "quantile" method to insure the commen reference have the same distribution. But with dye swap, I can not use neither "Rquantile" nor "Gquantile". What should I do? Or other normalization suggestions? Regards, Yanju Zhang
Microarray Microarray • 865 views
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@jdelasherasedacuk-1189
Last seen 9.3 years ago
United Kingdom
Quoting yanju <yanju at="" liacs.nl="">: > Hello All, > > my microarray datasets are like follows. And I want to normalize the data. > Targets: > Sample FileName Dye Stage Cy3 Cy5 > ZWS57 57.gpr T5C3 high oblong ref high > ZWS58 58.gpr T3C5 high oblong high ref > ZWS61 61.gpr T5C3 high oblong ref high > ZWS62 62.gpr T3C5 high oblong high ref > > ref is the commen reference. First I think Within Array Normalization is > not neccesary (am i right?). Then I want to do the Between Array > Normalization using "quantile" method to insure the commen reference > have the same distribution. But with dye swap, I can not use neither > "Rquantile" nor "Gquantile". What should I do? Or other normalization > suggestions? > > Regards, > Yanju Zhang Hi Yanju, why do you think you don't need to normalise within arrays? In a 2-colour array experiment, within-array normalisation is usually the one normalisation that's required... but maybe I'm missing something about your experiment? Unless your data have an unusual distribution, probably print-tip loess normalisation (this is within array, of course) will be appropriate. It looks like you're using 'limma', and your targets file indicates the orientation of the hybs, which then will be reflected in the design matrix... the linear model fit will take care of teh dye swaps. You can also add a "Dye Effect" coefficient to be calculated, if you wish. The Limma Users Guide contains some nice examples about this. Jose -- Dr. Jose I. de las Heras Email: J.delasHeras at ed.ac.uk The Wellcome Trust Centre for Cell Biology Phone: +44 (0)131 6513374 Institute for Cell & Molecular Biology Fax: +44 (0)131 6507360 Swann Building, Mayfield Road University of Edinburgh Edinburgh EH9 3JR UK
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