![]() ![]() Note that when you request glider data, you will often receive GPS data files as part of the response. This bug was fixed in R2017a, and there is a workaround for earlier versions. If you plan on accessing the NetCDF files directly from the server with your Matlab script, rather than downloading them, please note that there is a bug in earlier versions of Matlab that prevents accessing datasets from OPeNDAP severs that use HTTPS, like the OOI Data Portal. Note that many probes will have "NA" for gene symbol and Entrez ID. This produces a tab-delimited text file of the following format. Write.table(rma, file = "rma.txt", quote = FALSE, sep = "\t", row.names = FALSE, col.names = TRUE) #Write RMA-normalized, mapped data to file Symbols = unlist(mget(probes, hugene10sttranscriptclusterSYMBOL, ifnotfound=NA))Įntrez_IDs = unlist(mget(probes, hugene10sttranscriptclusterENTREZID, ifnotfound=NA)) #Extract probe ids, entrez symbols, and entrez ids Ls("package:hugene10sttranscriptcluster.db") #Annotations at the transcript-cluster level (more gene-centric view) Ls("package:hugene10stprobeset.db") #Annotations at the exon probeset level #To see all available mappings for this platform ![]() #Map probe sets to gene symbols or other annotations #Get the important stuff out of the data - the expression estimates for each array #perform RMA normalization (I would normally use GCRMA but it did not work with this chip) Raw.data=ReadAffy(verbose=TRUE, filenames=cels, cdfname="hugene10stv1") #From bioconductor Setwd("/Users/ogriffit/Dropbox/BioStars/GSE27447/data") Sapply(paste("data", cels, sep="/"), gunzip) Setwd("/Users/ogriffit/Dropbox/BioStars/GSE27447")Ĭels = list.files("data/", pattern = "CEL") #Download the CEL file package for this dataset (by GSE - Geo series id) Setwd("/Users/ogriffit/Dropbox/BioStars") # install additional bioconductor libraries, if not already installedīiocLite("hugene10sttranscriptcluster.db") #install the core bioconductor packages, if not already installed It assumes you have latest version of R installed and will have to change some working directories. This is how I would process that particular dataset in R/Bioconductor. ![]()
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