Hi Johannes and thanks for your reply. The PietrLand.csv file is the file that contains the gene name, regulation (-1,1 down, up), the Breed(Pietrain=1, Landrace=2) and the Time (1,2,3,..7 which stands for 2,4,8,12,16,24,30 hours that the samples were taken respectively). Each gene was down or up regulated at different time points per breed and I want to have these info in a table. To be more specific : > PL<-read.csv("PietrLand.csv",header=TRUE) > dim(PL) [1] 6236 4 > class(PL) [1] "data.frame" > PL[1:4,] Gene.name Regulation Breed Time 1 Ssc.7157.1.A1_at 1 1 1 2 Ssc.9062.1.A1_at 1 1 1 3 Ssc.14467.2.S1_a_at 1 1 1 4 Ssc.19413.1.A1_at 1 1 1 > q<-table(PL[,c(1,4)]) > dim(q) [1] 2568 7 > q[1:4,] Time Gene.name 1 2 3 4 5 6 7 AFFX-Ss_IRP_3_at 1 1 2 0 0 1 1 AFFX-Ss_IRP_5_at 0 0 1 0 0 0 0 AFFX-Ss_IRP_M_at 0 0 1 0 0 0 0 AFFX-SSC-28SrRNA_at 0 0 1 0 1 1 0 What I would like to have is a combination of Time-Breed information per gene. As you can notice at different time points genes are differentially expressed ( up-down regulated) and I want to keep track of the gene behaviour per breed. More specifically sth like this : Gene.name Breed1 Breed 2 Time min Time max Time min Time max AFFX-Ss_IRP_3_at 2 4 2 5 AFFX-Ss_IRP_5_at 1 6 3 7 This info mean for example the first gene that the gene was appearing down regulated at time point 2 and up regulated for time 4 for the first breed and that the gene was appearing down reg. at time point 2 and up regulated for time point 5 for the second breed. The resulting table should have 2568 X 4 dimensions. I thought about using the function apply() but it needs a matrix and this is not a matrix. Cheers, Daphne

Hi Daphne, can you convert q into a matrix using as.matrix()? For example: > q<-as.matrix(table(PL[,c(1,4)])) Also, you can always use apply() to make a quick-and-dirty for-loop. For example > x <- matrix(rnorm(100), 10) > apply(matrix(1:10), 1, function(i) mean(x[i,])) #row means [1] 0.36618487 -0.27148188 0.22449872 0.36215196 0.15594956 0.16164272 0.05519145 -0.17158213 [9] -0.19026337 -0.12838692 > y <- matrix(rnorm(100),10) > apply(matrix(1:10), 1, function(i) cor(x[i,], y[i,])) #row-wise correlation between x and y [1] -0.569887927 0.008844097 -0.602930234 -0.092437966 0.074451523 0.099452783 0.199365306 [8] -0.427166116 -0.488460859 -0.134369206 This is ugly on so many levels but sometimes it saves me a lot of programming time. Of course, at least for the first example, there is a much better solution: > rowMeans(x) [1] 0.36618487 -0.27148188 0.22449872 0.36215196 0.15594956 0.16164272 0.05519145 -0.17158213 [9] -0.19026337 -0.12838692 Best, --Johannes Johannes Freudenberg Graduate Student Division of Biomedical Informatics TCHRF 8526 Cincinnati Children's Hospital Medical Center 3333 Burnet Avenue Cincinnati, OH 45229 phone: (513) 636-1424 fax: (513) 636-2056 e-mail: johannes.freudenberg at cchmc.org >>> "daphne mouzaki (RI)" <daphne.mouzaki at="" bbsrc.ac.uk=""> 09/23/06 7:43 AM >>> Hi Johannes and thanks for your reply. The PietrLand.csv file is the file that contains the gene name, regulation (-1,1 down, up), the Breed(Pietrain=1, Landrace=2) and the Time (1,2,3,..7 which stands for 2,4,8,12,16,24,30 hours that the samples were taken respectively). Each gene was down or up regulated at different time points per breed and I want to have these info in a table. To be more specific : > PL<-read.csv("PietrLand.csv",header=TRUE) > dim(PL) [1] 6236 4 > class(PL) [1] "data.frame" > PL[1:4,] Gene.name Regulation Breed Time 1 Ssc.7157.1.A1_at 1 1 1 2 Ssc.9062.1.A1_at 1 1 1 3 Ssc.14467.2.S1_a_at 1 1 1 4 Ssc.19413.1.A1_at 1 1 1 > q<-table(PL[,c(1,4)]) > dim(q) [1] 2568 7 > q[1:4,] Time Gene.name 1 2 3 4 5 6 7 AFFX-Ss_IRP_3_at 1 1 2 0 0 1 1 AFFX-Ss_IRP_5_at 0 0 1 0 0 0 0 AFFX-Ss_IRP_M_at 0 0 1 0 0 0 0 AFFX-SSC-28SrRNA_at 0 0 1 0 1 1 0 What I would like to have is a combination of Time-Breed information per gene. As you can notice at different time points genes are differentially expressed ( up-down regulated) and I want to keep track of the gene behaviour per breed. More specifically sth like this : Gene.name Breed1 Breed 2 Time min Time max Time min Time max AFFX-Ss_IRP_3_at 2 4 2 5 AFFX-Ss_IRP_5_at 1 6 3 7 This info mean for example the first gene that the gene was appearing down regulated at time point 2 and up regulated for time 4 for the first breed and that the gene was appearing down reg. at time point 2 and up regulated for time point 5 for the second breed. The resulting table should have 2568 X 4 dimensions. I thought about using the function apply() but it needs a matrix and this is not a matrix. Cheers, Daphne _______________________________________________ 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