Hi all, I am using normalize.quantiles in package preprocessCore to deal with my data now, and when I am trying to average the expression value of each chip to visualize the result of quantile normalization, I curiously found one chip seem to have a different average expression value from others. I have uploaded the image to imageshack: http://img685.imageshack.us/img685/8320/mean.gif It is noted that the average expression value of case no.184 is clearly away from other cases. After checking the normalized data, I have found two cells which seemed should be 2.287524785 and 2.287870326 are replaced with both 2.28769392. I am not sure what is causing the problem, and have tried the normalization on two different computers, one with R 2.9.1 and preprocessCore 1.6 on a x64 system, and the other with R 2.10.1 and preprocessCore 1.8.0 on a x86 system. However the results are identical. My code is as follows: library(preprocessCore) alldata.q=as.matrix(alldata) alldata.q=normalize.quantiles(alldata.q) alldata.q=data.frame(alldata.q) row.names(alldata.q)=row.names(alldata) names(alldata.q)=names(alldata) plot(mean(alldata.q)) And to specify which is the different spot, I have used another code: mean(alldata.q)==mean(alldata.q)[1] And the result are all TRUEs, except one FALSE for case no.184. I am not sure if there is an error in my code, or really in the function itself. In order to reproduce the error to have further information, I have uploaded the data somewhere else, since I think it unlikely possible to attach a file as big as 31mb. Please find the file in following url: http://webhd.ndmctsgh.edu.tw/invite/tw/webhd/bNzQ5OS85ODkxNi8xMjcxNDEx NjEw If any further information is needed to clearify the problem, please let me know. kindest regards, Tseng, Chih-hao --==Mailed via NDMCTSGH Webmail==--

Without actually looking at your data, a reasonable explanation for what you have observed would be in the handling of ties. The algorithm ensures that values that are equal on input in a given column are also equal on output. > set.seed(1) > X <- rnorm(100000) > X <- round(X,3) ### This creates a bunch of non-unique values. > X <- matrix(X,ncol=10) > library(preprocessCore) > X.norm <- normalize.quantiles(X) > colMeans(X.norm) [1] -0.00224544 -0.00224477 -0.00224519 -0.00224287 -0.00224322 -0.00224448 [7] -0.00224846 -0.00224612 -0.00224265 -0.00224595 > set.seed(1) > X <- rnorm(100000) > X <- matrix(X,ncol=10) ## no rounding here so every value is unique > X.norm <- normalize.quantiles(X) > colMeans(X.norm) [1] -0.002244083 -0.002244083 -0.002244083 -0.002244083 -0.002244083 [6] -0.002244083 -0.002244083 -0.002244083 -0.002244083 -0.002244083 > > Hi all, > > I am using normalize.quantiles in package preprocessCore > to deal with my data now, and when I am trying to average > the expression value of each chip to visualize the result > of quantile normalization, I curiously found one chip seem > to have a different average expression value from others. I > have uploaded the image to imageshack: > http://img685.imageshack.us/img685/8320/mean.gif > It is noted that the average expression value of case no.184 > is clearly away from other cases. > > After checking the normalized data, I have found two > cells which seemed should be 2.287524785 and 2.287870326 > are replaced with both 2.28769392. I am not sure what is > causing the problem, and have tried the normalization on > two different computers, one with R 2.9.1 and preprocessCore > 1.6 on a x64 system, and the other with R 2.10.1 and > preprocessCore 1.8.0 on a x86 system. However the results > are identical. My code is as follows: > > library(preprocessCore) > alldata.q=as.matrix(alldata) > alldata.q=normalize.quantiles(alldata.q) > alldata.q=data.frame(alldata.q) > row.names(alldata.q)=row.names(alldata) > names(alldata.q)=names(alldata) > plot(mean(alldata.q)) > > And to specify which is the different spot, I have used > another code: > > mean(alldata.q)==mean(alldata.q)[1] > > And the result are all TRUEs, except one FALSE for case > no.184. I am not sure if there is an error in my code, or > really in the function itself. > > In order to reproduce the error to have further information, I > have uploaded the data somewhere else, since I think it unlikely > possible to attach a file as big as 31mb. Please find the file in > following url: > http://webhd.ndmctsgh.edu.tw/invite/tw/webhd/bNzQ5OS85ODkxNi8xMjcxND ExNjEw > > If any further information is needed to clearify the problem, please > let me know. > > kindest regards, > Tseng, Chih-hao > > > --==Mailed via NDMCTSGH Webmail==-- > > _______________________________________________ > 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 >

you're looking at differences of the order 1e-10. look at boxplot(alldata.q), and if you must compare the means, try: means <- colMeans(alldata.q) names(means) <- NULL sapply(means, function(x) all.equal(x, means[1])) b On Fri, Apr 16, 2010 at 3:15 PM, 697820169 <697820169 at mail.ndmctsgh.edu.tw> wrote: > > Hi all, > > ?I am using normalize.quantiles in package preprocessCore > to deal with my data now, and when I am trying to average > the expression value of each chip to visualize the result > of quantile normalization, I curiously found one chip seem > to have a different average expression value from others. I > have uploaded the image to imageshack: > http://img685.imageshack.us/img685/8320/mean.gif > It is noted that the average expression value of case no.184 > is clearly away from other cases. > > ?After checking the normalized data, I have found two > cells which seemed should be 2.287524785 and 2.287870326 > are replaced with both 2.28769392. I am not sure what is > causing the problem, and have tried the normalization on > two different computers, one with R 2.9.1 and preprocessCore > 1.6 on a x64 system, and the other with R 2.10.1 and > preprocessCore 1.8.0 on a x86 system. However the results > are identical. My code is as follows: > > library(preprocessCore) > alldata.q=as.matrix(alldata) > alldata.q=normalize.quantiles(alldata.q) > alldata.q=data.frame(alldata.q) > row.names(alldata.q)=row.names(alldata) > names(alldata.q)=names(alldata) > plot(mean(alldata.q)) > > And to specify which is the different spot, I have used > another code: > > mean(alldata.q)==mean(alldata.q)[1] > > And the result are all TRUEs, except one FALSE for case > no.184. I am not sure if there is an error in my code, or > really in the function itself. > > ?In order to reproduce the error to have further information, I > have uploaded the data somewhere else, since I think it unlikely > possible to attach a file as big as 31mb. Please find the file in > following url: > http://webhd.ndmctsgh.edu.tw/invite/tw/webhd/bNzQ5OS85ODkxNi8xMjcxND ExNjEw > > If any further information is needed to clearify the problem, please > let me know. > > kindest regards, > Tseng, Chih-hao > > > --==Mailed via NDMCTSGH Webmail==-- > > _______________________________________________ > 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 >