Hi Andrea, I think your problem is with the min.obs argument. See ?p.vector. Given the dimensions below, you don't have 20 observations for each gene in Data. Valerie On 05/30/11 07:34, andrea.grilli at ior.it wrote: > Hi all, > I'm performing time series experiment with maSigPro package. When I > compute regression fit to find significant genes with "p.vector" > function, I receive this output: > Error: subscript out of bounds > > Here you can find a resume of my script: > library("maSigPro") > parameters <- as.matrix(read.table("./Parameters.txt", header = TRUE)) > # design object > design <- make.design.matrix (parameters, degree = 3) > Data <- read.table("./Data_RMAnorm.txt") # expression object > fit <- p.vector(Data, design, Q = 0.05, MT.adjust = "BH", min.obs = 20) >> Error: subscript out of bounds > > It looks like no right dimension of either design or array objects, > but both input files look ok for me. > >> parameters > Time Replicates Transfectant wt22 wt36 Saos1 Saos2 > CD99wt22_g21 21 1 1 1 0 0 0 > CD99wt22_g7 7 2 1 1 0 0 0 > CD99wt22_g0 0 5 1 1 0 0 0 > CD99wt22_g14 14 5 1 1 0 0 0 > CD99wt36_g21 21 1 1 0 1 0 0 > CD99wt36_g7 7 2 1 0 1 0 0 > CD99wt36_g0 0 6 1 0 1 0 0 > CD99wt36_g14 14 6 1 0 1 0 0 > Saos_g21_1 21 3 0 0 0 1 0 > Saos_g7_1 7 4 0 0 0 1 0 > Saos_g0_1 0 7 0 0 0 1 0 > Saos_g14_1 14 8 0 0 0 1 0 > Saos_g21_2 21 3 0 0 0 0 1 > Saos_g7_2 7 4 0 0 0 0 1 > Saos_g0_2 0 7 0 0 0 0 1 > Saos_g14_2 14 8 0 0 0 0 1 > >> ncol(parameters) > [1] 7 >> nrow(parameters) > [1] 16 >> typeof(parameters) > [1] "integer >> str(parameters) > int [1:16, 1:7] 21 7 0 14 21 7 0 14 21 7 ... > - attr(*, "dimnames")=List of 2 > ..$ : chr [1:16] "CD99wt22_g21" "CD99wt22_g7" "CD99wt22_g0" > "CD99wt22_g14" ... > ..$ : chr [1:7] "Time" "Replicates" "Transfectant" "wt22" ... >> rownames(parameters) > [1] "CD99wt22_g21" "CD99wt22_g7" "CD99wt22_g0" "CD99wt22_g14" > "CD99wt36_g21" > [6] "CD99wt36_g7" "CD99wt36_g0" "CD99wt36_g14" "Saos_g21_1" > "Saos_g7_1" > [11] "Saos_g0_1" "Saos_g14_1" "Saos_g21_2" "Saos_g7_2" > "Saos_g0_2" > [16] "Saos_g14_2" > > >> head(Data) > CD99wt22_g21 CD99wt22_g7 CD99wt22_g0 CD99wt22_g14 CD99wt36_g21 > 1007_s_at 8.700365 9.270211 9.430757 9.538669 8.745657 > 1053_at 9.147460 9.271868 9.313653 9.474059 9.070484 > 117_at 5.525772 5.295018 5.324190 5.616462 5.426015 > 121_at 7.677000 7.969068 7.808228 8.013086 7.710776 > 1255_g_at 3.006305 3.081713 2.978214 2.996469 2.962183 > 1294_at 6.062574 6.479575 6.162924 6.582346 6.189861 > CD99wt36_g7 CD99wt36_g0 CD99wt36_g14 Saos_g21_1 Saos_g7_1 > Saos_g0_1 > 1007_s_at 9.467785 9.496628 9.481157 9.103450 9.350170 > 9.746269 > 1053_at 9.238156 9.558520 9.402085 9.063520 8.932865 > 9.255722 > 117_at 5.724291 5.123912 5.656858 5.283452 5.438294 > 5.243948 > 121_at 8.105691 8.089829 8.109542 7.770491 7.984196 > 7.869393 > 1255_g_at 3.077948 2.986192 2.864020 2.954144 2.876680 > 2.858667 > 1294_at 6.307993 6.206513 6.688947 6.326808 6.327603 > 5.995019 > Saos_g14_1 Saos_g21_2 Saos_g7_2 Saos_g0_2 Saos_g14_2 > 1007_s_at 9.769688 9.107356 9.368514 9.613215 9.808061 > 1053_at 9.475658 9.040339 8.939737 9.228254 9.419188 > 117_at 5.556138 5.203474 5.432353 5.437419 5.546174 > 121_at 8.141229 7.663640 7.873487 7.908378 8.231635 > 1255_g_at 3.064729 2.905118 2.911833 2.959471 3.147845 > 1294_at 6.752825 6.373275 6.308702 6.041707 6.706011 >> ncol(Data) > [1] 16 >> nrow(Data) > [1] 54675 >> typeof(Data) > [1] "list" >> colnames(Data) > [1] "CD99wt22_g21" "CD99wt22_g7" "CD99wt22_g0" "CD99wt22_g14" > "CD99wt36_g21" > [6] "CD99wt36_g7" "CD99wt36_g0" "CD99wt36_g14" "Saos_g21_1" > "Saos_g7_1" > [11] "Saos_g0_1" "Saos_g14_1" "Saos_g21_2" "Saos_g7_2" > "Saos_g0_2" > [16] "Saos_g14_2" > > Data table comes from previous write.table after import of .CEL files > with ReadAffy and RMA normalization (from affymetryx platform > HG-U133_Plus_2). > R version is 2.11.1, instead maSigPro is 1.24.1. > > I focus that I'm new to Bioconductor, so I hope problem is clear.... > Any idea about possible solutions?? > > Thanks in advance, > Andrea > > _______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor

Hi Valerie, problem was exaclty number of observations: I tried with "min.obs" between 3 to 8 and everything worked fine. Maria Jos? Nueda (who created the package) also suggested this semplification of my experimental design: Time Replicates Transfectant Saos CD99wt22_g21 21 1 1 0 CD99wt22_g7 7 2 1 0 CD99wt22_g0 0 3 1 0 CD99wt22_g14 14 4 1 0 CD99wt36_g21 21 1 1 0 CD99wt36_g7 7 2 1 0 CD99wt36_g0 0 3 1 0 CD99wt36_g14 14 4 1 0 Saos_g21_1 21 5 0 1 Saos_g7_1 7 6 0 1 Saos_g0_1 0 7 0 1 Saos_g14_1 14 8 0 1 Saos_g21_2 21 5 0 1 Saos_g7_2 7 6 0 1 Saos_g0_2 0 7 0 1 Saos_g14_2 14 8 0 1 I hope this suggestion could be useful for futur users... Thanks to all for the support, Andrea Citando Valerie Obenchain <vobencha at="" fhcrc.org="">: > Hi Andrea, > > I think your problem is with the min.obs argument. See ?p.vector. > > Given the dimensions below, you don't have 20 observations for each > gene in Data. > > Valerie > > > On 05/30/11 07:34, andrea.grilli at ior.it wrote: >> Hi all, >> I'm performing time series experiment with maSigPro package. When I >> compute regression fit to find significant genes with "p.vector" >> function, I receive this output: >> Error: subscript out of bounds >> >> Here you can find a resume of my script: >> library("maSigPro") >> parameters <- as.matrix(read.table("./Parameters.txt", header = >> TRUE)) # design object >> design <- make.design.matrix (parameters, degree = 3) >> Data <- read.table("./Data_RMAnorm.txt") # expression object >> fit <- p.vector(Data, design, Q = 0.05, MT.adjust = "BH", min.obs = 20) >>> Error: subscript out of bounds >> >> It looks like no right dimension of either design or array objects, >> but both input files look ok for me. >> >>> parameters >> Time Replicates Transfectant wt22 wt36 Saos1 Saos2 >> CD99wt22_g21 21 1 1 1 0 0 0 >> CD99wt22_g7 7 2 1 1 0 0 0 >> CD99wt22_g0 0 5 1 1 0 0 0 >> CD99wt22_g14 14 5 1 1 0 0 0 >> CD99wt36_g21 21 1 1 0 1 0 0 >> CD99wt36_g7 7 2 1 0 1 0 0 >> CD99wt36_g0 0 6 1 0 1 0 0 >> CD99wt36_g14 14 6 1 0 1 0 0 >> Saos_g21_1 21 3 0 0 0 1 0 >> Saos_g7_1 7 4 0 0 0 1 0 >> Saos_g0_1 0 7 0 0 0 1 0 >> Saos_g14_1 14 8 0 0 0 1 0 >> Saos_g21_2 21 3 0 0 0 0 1 >> Saos_g7_2 7 4 0 0 0 0 1 >> Saos_g0_2 0 7 0 0 0 0 1 >> Saos_g14_2 14 8 0 0 0 0 1 >> >>> ncol(parameters) >> [1] 7 >>> nrow(parameters) >> [1] 16 >>> typeof(parameters) >> [1] "integer >>> str(parameters) >> int [1:16, 1:7] 21 7 0 14 21 7 0 14 21 7 ... >> - attr(*, "dimnames")=List of 2 >> ..$ : chr [1:16] "CD99wt22_g21" "CD99wt22_g7" "CD99wt22_g0" >> "CD99wt22_g14" ... >> ..$ : chr [1:7] "Time" "Replicates" "Transfectant" "wt22" ... >>> rownames(parameters) >> [1] "CD99wt22_g21" "CD99wt22_g7" "CD99wt22_g0" "CD99wt22_g14" >> "CD99wt36_g21" >> [6] "CD99wt36_g7" "CD99wt36_g0" "CD99wt36_g14" "Saos_g21_1" "Saos_g7_1" >> [11] "Saos_g0_1" "Saos_g14_1" "Saos_g21_2" "Saos_g7_2" "Saos_g0_2" >> [16] "Saos_g14_2" >> >> >>> head(Data) >> CD99wt22_g21 CD99wt22_g7 CD99wt22_g0 CD99wt22_g14 CD99wt36_g21 >> 1007_s_at 8.700365 9.270211 9.430757 9.538669 8.745657 >> 1053_at 9.147460 9.271868 9.313653 9.474059 9.070484 >> 117_at 5.525772 5.295018 5.324190 5.616462 5.426015 >> 121_at 7.677000 7.969068 7.808228 8.013086 7.710776 >> 1255_g_at 3.006305 3.081713 2.978214 2.996469 2.962183 >> 1294_at 6.062574 6.479575 6.162924 6.582346 6.189861 >> CD99wt36_g7 CD99wt36_g0 CD99wt36_g14 Saos_g21_1 Saos_g7_1 Saos_g0_1 >> 1007_s_at 9.467785 9.496628 9.481157 9.103450 9.350170 >> 9.746269 >> 1053_at 9.238156 9.558520 9.402085 9.063520 8.932865 >> 9.255722 >> 117_at 5.724291 5.123912 5.656858 5.283452 5.438294 >> 5.243948 >> 121_at 8.105691 8.089829 8.109542 7.770491 7.984196 >> 7.869393 >> 1255_g_at 3.077948 2.986192 2.864020 2.954144 2.876680 >> 2.858667 >> 1294_at 6.307993 6.206513 6.688947 6.326808 6.327603 >> 5.995019 >> Saos_g14_1 Saos_g21_2 Saos_g7_2 Saos_g0_2 Saos_g14_2 >> 1007_s_at 9.769688 9.107356 9.368514 9.613215 9.808061 >> 1053_at 9.475658 9.040339 8.939737 9.228254 9.419188 >> 117_at 5.556138 5.203474 5.432353 5.437419 5.546174 >> 121_at 8.141229 7.663640 7.873487 7.908378 8.231635 >> 1255_g_at 3.064729 2.905118 2.911833 2.959471 3.147845 >> 1294_at 6.752825 6.373275 6.308702 6.041707 6.706011 >>> ncol(Data) >> [1] 16 >>> nrow(Data) >> [1] 54675 >>> typeof(Data) >> [1] "list" >>> colnames(Data) >> [1] "CD99wt22_g21" "CD99wt22_g7" "CD99wt22_g0" "CD99wt22_g14" >> "CD99wt36_g21" >> [6] "CD99wt36_g7" "CD99wt36_g0" "CD99wt36_g14" "Saos_g21_1" "Saos_g7_1" >> [11] "Saos_g0_1" "Saos_g14_1" "Saos_g21_2" "Saos_g7_2" "Saos_g0_2" >> [16] "Saos_g14_2" >> >> Data table comes from previous write.table after import of .CEL >> files with ReadAffy and RMA normalization (from affymetryx platform >> HG-U133_Plus_2). >> R version is 2.11.1, instead maSigPro is 1.24.1. >> >> I focus that I'm new to Bioconductor, so I hope problem is clear.... >> Any idea about possible solutions?? >> >> Thanks in advance, >> Andrea >> >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor at r-project.org >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: >> http://news.gmane.org/gmane.science.biology.informatics.conductor Dr. Andrea Grilli andrea.grilli at ior.it phone 051/63.66.756 Laboratory of Experimental Oncology Rizzoli Orthopaedic Institute Codivilla Putti Research Center via di Barbiano 1/10 40136 - Bologna - Italy