similar to: read.table

Displaying 5 results from an estimated 5 matches similar to: "read.table"

2017 Jun 04
0
read.table
On 04.06.2017 11:50, jing hua zhao wrote: > Hi All, > > > I wonder if there should be one character for quote= in read.table, i.e., > > >> args(read.table) > function (file, header = FALSE, sep = "", quote = "\"'", dec = ".", > ... > > I have a file containing the following lines, > > > 08248-GOTERM
2007 Mar 01
1
object is not subsettable
Dear colleagues, I've just come across a problem with the following command which is a part of the "metaOverview.R" code file provided as an monography- accompanying file at http://www.bioconductor.org/docs/mogr/metadata: ################################## R> hasChr <- eapply(GOTERM, function(x) + x[grep("chromosome", Term(x))]) Error in
2005 May 04
1
error with the function GOHyperG from GOstats package
I am running R 2.0.0, GOstats 1.1.1 and GO 1.7.0, and when I use the function GOHyperG, I have the following error: w1<-as.list(hgu95av2LOCUSID) w2<-unique(unlist(w1)) set.seed(123) myLL<-sample(w2,100) xx <- GOHyperG(myLL) Error in mget(x, env = GOTERM, ifnotfound = NA) : recursive default argument reference In fact first I tried this function with my locusId ' list (with
2005 Mar 30
1
Installing GO 1.7.0
I'm in the process of packaging R (and R modules) for future inclusion in Fedora Extras, and I've managed to get several hundred modules installed without issue, however, the GO metadata package is refusing to comply. Since I'm packaging this in rpm format, I can't use any of the automated functions for build, I've got to do it locally through R. The following steps work for
2011 Sep 13
2
GO & Protein Complex Analysis for Homo sapiens
Dear All, I need to fetch GO ontologies for Homo sapiens with their mappings to corresponding Uniprot identifiers. I would be using this information to compare result from a clustering algorithm with existing protein complexes. This would be a test to check how the clustering algorithm accurately captures GO terms with respect to the known protein complexes. Can anyone suggest a simple workflow