timecourse package - Missing data
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Marcelo Laia ▴ 450
@marcelo-laia-2007
Last seen 3.1 years ago
Brazil
>From the timecourse vignete: "For version 1.0.0, missing time point samples are not allowed inmb.long() andmb.MANOVA(), while missing replicates are allowed for a subset of genes." Is this missing data only allowed for a subset of genes or for a whole replicate? We have a data set with 5 times points: time0 - animal 1, animal 2, and animal 3 time1 - animal 4, animal 5, and animal 6 time2 - animal 7, and animal 8 time3 - animal 9, animal 10, animal 11 time4 - animal 12, animal 13, animal 14 So, time 2 has only 2 replicates. I try this code: > assay <- c("d1", "d1", "d1", "d1", "d2", "d2", "d2", "d2", "d2", "d3", "d3", "d3", "d3", "d3") > time.grp <- c(1, 2, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5) > time.grp > dim(todos.timecourse.matrix) [1] 9600 14 > size <- read.table("reps.csv", sep="\t", header=TRUE) > size.matrix = size[,2:6] > row.names(size.matrix) = size[,1] > size.matrix[1:10,] T0 T1 T2 T3 T4 gene1 3 3 2 3 3 gene2 3 3 2 3 3 gene3 3 3 2 3 3 gene4 3 3 2 3 3 gene5 3 3 2 3 3 gene6 3 3 2 3 3 gene7 3 3 2 3 3 gene8 3 3 2 3 3 gene9 3 3 2 3 3 gene10 3 3 2 3 3 > > out1 <- mb.long(todos.timecourse.matrix, times = 5, reps = size.matrix, + rep.grp = assay, time.grp = time.grp, HotellingT2.only = FALSE) Error in mb.1D(object, times, reps, prior.df, prior.COV, prior.eta, time.grp, : The sample sizes are incorrect. > Are there a way to analysis this data on timecourse package? Am I doing any mistake or misinterpretation? Thank you very much -- Marcelo Luiz de Laia Brazil Linux user number 487797
TimeCourse timecourse TimeCourse timecourse • 1.3k views
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Yu Chuan Tai ▴ 440
@yu-chuan-tai-1534
Last seen 10.2 years ago
Hi Marcelo, The current version of Timecourse is for longitudinal time course data only. Based on what you described below, your study looked like a cross-sectional one because time point samples were from different animals. That's, they were independent. I'd suggest that you use other software for analyzing your data, e.g. limma. The cross-sectional method will be built in timecourse in the future. Best, Yu Chuan On Mon, 8 Feb 2010, Marcelo Laia wrote: >> From the timecourse vignete: > > "For version 1.0.0, missing time point samples are not allowed > inmb.long() andmb.MANOVA(), > while missing replicates are allowed for a subset of genes." > > Is this missing data only allowed for a subset of genes or for a whole > replicate? > > We have a data set with 5 times points: > > time0 - animal 1, animal 2, and animal 3 > time1 - animal 4, animal 5, and animal 6 > time2 - animal 7, and animal 8 > time3 - animal 9, animal 10, animal 11 > time4 - animal 12, animal 13, animal 14 > > So, time 2 has only 2 replicates. > > I try this code: > >> assay <- c("d1", "d1", "d1", "d1", "d2", "d2", "d2", "d2", "d2", > "d3", "d3", "d3", "d3", "d3") > >> time.grp <- c(1, 2, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5) >> time.grp > >> dim(todos.timecourse.matrix) > [1] 9600 14 > >> size <- read.table("reps.csv", sep="\t", header=TRUE) >> size.matrix = size[,2:6] >> row.names(size.matrix) = size[,1] > >> size.matrix[1:10,] > T0 T1 T2 T3 T4 > gene1 3 3 2 3 3 > gene2 3 3 2 3 3 > gene3 3 3 2 3 3 > gene4 3 3 2 3 3 > gene5 3 3 2 3 3 > gene6 3 3 2 3 3 > gene7 3 3 2 3 3 > gene8 3 3 2 3 3 > gene9 3 3 2 3 3 > gene10 3 3 2 3 3 >> > >> out1 <- mb.long(todos.timecourse.matrix, times = 5, reps = size.matrix, > + rep.grp = assay, time.grp = time.grp, > HotellingT2.only = FALSE) > Error in mb.1D(object, times, reps, prior.df, prior.COV, prior.eta, > time.grp, : > The sample sizes are incorrect. >> > > > Are there a way to analysis this data on timecourse package? > > Am I doing any mistake or misinterpretation? > > Thank you very much > > -- > Marcelo Luiz de Laia > Brazil > Linux user number 487797 > > _______________________________________________ > 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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2010/2/10 Yu Chuan Tai <yuchuan at="" stat.berkeley.edu="">: > Hi Marcelo, > > The current version of Timecourse is for longitudinal time course data only. > Based on what you described below, your study looked like a cross- sectional > one because time point samples were from different animals. That's, they > were independent. I'd suggest that you use other software for analyzing your > data, e.g. limma. > The cross-sectional method will be built in timecourse in the future. > > Best, > Yu Chuan Hi Yu Chuan, Thank you very much for help me! I had thought that my data could be analyzed by timecourse package. Sorry. I already have tried limma... I do all contrasts (T1-T0, T2-T0, T2-T1, ...), but, I would like to see a graph "expression (y) by time (x)" for all DE genes. Have you (or others members) any suggestion on how I could do that? I already have looked at maSigPro, too. Thank you very much! -- Marcelo Luiz de Laia Brazil Linux user number 487797
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