################################################## # # Dave Gerrard, University of Manchester # 2011 # # ################################################## # R scripts to analyse Cliff Rowe's Liver Protein dataset. There is quite a bit of setting up of directories and R packages before running the scripts. It would be best to have the same version of R (or later?) A master script called LiverProtsAnalysisMaster.R lists the other scripts and can be used to call them. ## RUNNING THE SCRIPTS. LiverProteins dependencies and packages. #### SESSION INFO (these are the packages loaded by the end of the process. > sessionInfo() R version 2.11.1 (2010-05-31) i386-pc-mingw32 locale: [1] LC_COLLATE=English_United Kingdom.1252 LC_CTYPE=English_United Kingdom.1252 LC_MONETARY=English_United Kingdom.1252 [4] LC_NUMERIC=C LC_TIME=English_United Kingdom.1252 attached base packages: [1] grid stats graphics grDevices utils datasets methods base other attached packages: [1] org.Hs.eg.db_2.4.1 qvalue_1.24.0 gplots_2.8.0 caTools_1.10 bitops_1.0-4.1 [6] gdata_2.8.0 gtools_2.6.2 lattice_0.18-8 topGO_1.16.2 SparseM_0.88 [11] GO.db_2.4.1 RSQLite_0.9-2 DBI_0.2-5 AnnotationDbi_1.10.2 Biobase_2.8.0 [16] graph_1.28.0 loaded via a namespace (and not attached): [1] tcltk_2.11.1 tools_2.11.1 ### LIBRARIES # might be best to install bioconductor # source("http://bioconductor.org/biocLite.R") # biocLite() #install.packages(c("topGO", "lattice", "gplots", "qvalue", "org.Hs.eg.db")) # these may take some time. # explicitly loaded packages. These are loaded from the scripts.And need to have been installed library(topGO) library(lattice) require(gplots) library(qvalue) library(org.Hs.eg.db) # may be a bunch of dependencies to do with BioConductor and topGO. e.g. GO.db, AnnotationDbi ### INPUT FILES baseProteinByLiverSample <- read.delim("C:/Users/dave/LiverProteins/data/Cliffs dataset.txt", header=T) prot2go <- readMappings("C:/Users/dave/LiverProteins/data/go2prot.map") expDesignLiverProteins <- read.delim("C:/Users/dave/LiverProteins/data/CliffsExpDesign.txt", header=T) # this kappaMatrix can be recalculated as part of the script kappaMatrix <- read.delim("C:/Users/dave/LiverProteins/data/ubiProtsKappaMatrixDetected.tab",sep="\t",header=T) ### See LiverProtsAnalysisMaster.R for individual scripts.