"normalize.quantiles.robust" produces the SAME intensities from different weights?!
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k. brand ▴ 420
@k-brand-1874
Last seen 7.7 years ago
Dear BioCers, My interpretation of the function "normalize.quantiles.robust" is the ability to selectively increase or reduce the contribution of specific chips during normalization. Although i get different results from equally weighted chips (which is the same as "justRMA" as a verification), all variations of unequal weightings produce do the SAME intensities?! See 2 examples below. Can some one find the error in my script, or better yet, give an example of a better way to achieve my objective- to selectively 'pull' low intensities of duplicate chips form a poor hyb (on expired arrays), up to the levels of duplicate chips of a good hyb(on unexpired arrays). TIA, Karl >### "weight_is_1&10.R" > > setwd("D:/brand 8/CORE-SHELL/Diff methods/ID T0 all/normalisations/Quantiles-robust") > library(affy) > dat <- ReadAffy() > # list with weights for robust normalization > param <- list(weights=c(1,1,10,10,1,1,10,10,1,1,10,10)) > # performs robust quantile normalization > # summarization is performed using medianpolish > eset <- expresso(dat, bgcorrect.method="rma", + normalize.method="quantiles.robust", normalize.param=param, + pmcorrect.method="pmonly", summary.method = "medianpolish") background correction: rma normalization: quantiles.robust PM/MM correction : pmonly expression values: medianpolish background correcting...done. normalizing...Chip weights are 1 1 10 10 1 1 10 10 1 1 10 10 Chip weights are 1 1 10 10 1 1 10 10 1 1 10 10 done. 45101 ids to be processed | | |####################| > exprs2excel(eset, "weight_is_1&10.csv") > for probset 1415670_at 6.268887235 5.946937963 7.191120262 7.087367938 6.145685893 6.095744472 7.473473796 7.21058045 6.105367399 6.130141537 7.324310607 7.059578097 > ### "weight_is_10&1.R" > dat <- ReadAffy() > # list with weights for robust normalization > param <- list(weights=c(10,10,1,1,10,10,1,1,10,10,1,1)) > # performs robust quantile normalization > # summarization is performed using medianpolish > eset <- expresso(dat, bgcorrect.method="rma", + normalize.method="quantiles.robust", normalize.param=param, + pmcorrect.method="pmonly", summary.method = "medianpolish") background correction: rma normalization: quantiles.robust PM/MM correction : pmonly expression values: medianpolish background correcting...done. normalizing...Chip weights are 10 10 1 1 10 10 1 1 10 10 1 1 Chip weights are 10 10 1 1 10 10 1 1 10 10 1 1 done. 45101 ids to be processed | | |####################| > exprs2excel(eset, "weight_is_10&1.csv") for probset 1415670_at 6.268887235 5.946937963 7.191120262 7.087367938 6.145685893 6.095744472 7.473473796 7.21058045 6.105367399 6.130141537 7.324310607 7.059578097 ============================================================== > sessionInfo() Version 2.3.0 (2006-04-24) i386-pc-mingw32 attached base packages: [1] "tools" "methods" "stats" "graphics" "grDevices" "utils" [7] "datasets" "base" other attached packages: affyPLM gcrma matchprobes affydata mouse4302cdf affy "1.8.0" "2.4.1" "1.4.0" "1.8.0" "1.12.0" "1.10.0" affyio Biobase "1.0.0" "1.10.0" -- Karl Brand <k.brand at="" erasmusmc.nl=""> Department of Cell Biology and Genetics Erasmus MC Dr Molewaterplein 50 3015 GE Rotterdam lab +31 (0)10 408 7409 fax +31 (0)10 408 9468
Normalization affydata gcrma matchprobes affyPLM affyio Normalization affydata gcrma • 729 views
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Ben Bolstad ★ 1.2k
@ben-bolstad-1494
Last seen 4.7 years ago
Thanks for this report. It turned out that there was a minor bug in normalize.quantiles.robust() and incorrect parameters were being passed down to the C code. This is due to some changes I made many months ago now. A corrected version of the function will appear in the next version of affy. But briefly the final line in that function should have been: .Call("R_qnorm_robust_c",x,copy,weights,as.integer(use.median),as.int eger(use.log2),as.integer(use.huber),PACKAGE="affy") Best, Ben On Wed, 2006-09-20 at 17:29 +0200, k. brand wrote: > Dear BioCers, > > My interpretation of the function "normalize.quantiles.robust" is the > ability to selectively increase or reduce the contribution of specific > chips during normalization. > > Although i get different results from equally weighted chips (which is > the same as "justRMA" as a verification), all variations of unequal > weightings produce do the SAME intensities?! See 2 examples below. > > Can some one find the error in my script, or better yet, give an example > of a better way to achieve my objective- > > to selectively 'pull' low intensities of duplicate chips form a poor hyb > (on expired arrays), up to the levels of duplicate chips of a good > hyb(on unexpired arrays). > > TIA, > > Karl > >
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Ben, thank you for the fast help- it worked! Karl on 9/21/2006 5:16 AM Ben Bolstad said the following: > Thanks for this report. It turned out that there was a minor bug in > normalize.quantiles.robust() and incorrect parameters were being passed > down to the C code. This is due to some changes I made many months ago > now. > > A corrected version of the function will appear in the next version of > affy. But briefly the final line in that function should have been: > > > .Call("R_qnorm_robust_c",x,copy,weights,as.integer(use.median),as.i nteger(use.log2),as.integer(use.huber),PACKAGE="affy") > > Best, > > Ben > > On Wed, 2006-09-20 at 17:29 +0200, k. brand wrote: >> Dear BioCers, >> >> My interpretation of the function "normalize.quantiles.robust" is the >> ability to selectively increase or reduce the contribution of specific >> chips during normalization. >> >> Although i get different results from equally weighted chips (which is >> the same as "justRMA" as a verification), all variations of unequal >> weightings produce do the SAME intensities?! See 2 examples below. >> >> Can some one find the error in my script, or better yet, give an example >> of a better way to achieve my objective- >> >> to selectively 'pull' low intensities of duplicate chips form a poor hyb >> (on expired arrays), up to the levels of duplicate chips of a good >> hyb(on unexpired arrays). >> >> TIA, >> >> Karl >> >> > > -- Karl Brand <k.brand at="" erasmusmc.nl=""> Department of Genetics Erasmus MC Dr Molewaterplein 50 3015 GE Rotterdam lab +31 (0)10 408 7409 fax +31 (0)10 408 9468
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