search for: genelist

...993279 9.160038 9.104121 10.079177 9.828757 5 A_184 3.574271 4.680859 4.517047 4.047096 3.623668 3.021356 3.559434 3.156093 4.308437 4.045098 6 A_199 7.593952 7.454087 7.513013 7.449552 7.345718 7.367068 7.410085 7.022582 7.668616 7.953706 ... I tried to do it with a for loop: genelist <- read.delim("/user/R/raw_data.txt") rownames(genelist) <- genelist[,1] genes <- rownames(genelist) x <- 1:40000 set <- matrix(nrow = 50, ncol = 11) for(i in c(1:50)){ set[i] <-sample(x,50) print(c(i,"->", set), quote = FALSE) } which basical...

hi I want to compare two list by its names and get the values of that list. can anybody let me know the syntax of comparing the list by their names using a for loop c.genes<- list() for(i in 1:100) c.genes[[1]]<- geneset(which(geneset == tobecampared[i])) } here geneset is a list and also tobecampared is a list Thank you Ramya -- View this message in context:

Dear All: I tried to use heatmap.2 to generate hierarchical clustering using the following command: heatmap.2(datamatrix, scale="row", trace="none", col=greenred(256), labRow=genelist[,1], margins=c(10,10), Rowv=TRUE, Colv=TRUE) datamatrix is subset of a RMA normalized data subset by a genelist. The problem is a lot of times, the z-score in key are from, like -5 to 15 or -15 to 5, as a result, the zero of z distribution are are either green region or red region of the key, th...

Dear sir/madam, I have been using R for a while now for microarray analysis, and I would like to make a "master" data frame in which I can combine information from many different sources. The basic list a genelist with 25.000 probes, then I would like to have a subcompartment with the statistical information, a subcompartment with more extensive information regarding each gene, and then the output from several clustering programs, which group a number of genes and relate those to a function. In my mind this...

Hallo, > fit12<-lmFit(qrg[,1:2]) > t12<-toptable(fit12,adjust="fdr",number=25,genelist=qrg$genes[,1]) > t12 ID logFC t P.Value adj.P.Val B 522 PLAU_OP -6.836144 -8.420414 5.589416e-05 0.01212520 2.054965 1555 CD44_WIZ -6.569622 -8.227938 6.510169e-05 0.01212520 1.944046 Can anyone tell me what the difference is between P.Value and adj.P.Va...

...n object (GSint) \item \texttt{GSint2BC()} - Convert a GeneSpring gene expression object (GSint) to a BioConductor gene expression object (exprSet) \item \texttt{BC2GSint()} - Convert a BioConductor gene expression object (exprSet) to a GeneSpring gene expression object (GSint) \item \texttt{GSload.genelist()} - Read a GeneSpring GeneSpring gene list from file \item \texttt{GSsave.genelist()} - Save a GeneSpring GeneSpring gene list to file \item \texttt{GSsave.exp()} - Save a GeneSpring gene expression object (GSint) to file \end{itemize} For more information on using thi spackage with GeneSpring, g...

...4,5,5), dim1=c(1,0,1,0,1,0,1,0,1,0,1,0),dim2=c(0,1,0,1,0,1,0,1,0,1,0,1)) fit <- lmFit(normdata@maM, design) contrast.matrix<-makeContrasts(dim1vsdim2=dim2-dim1, levels=design) fit2 <- contrasts.fit(fit,contrast.matrix) fiteb <- eBayes(fit2) Toptable <- topTable(fiteb,number = 10600,genelist=maGeneTable(normdata), sort.by="P", resort.by= "M", adjust="BY") write.table(Toptable,file="RNG_Best_10000genes.txt", row.names=FALSE, col.names=TRUE, sep="\t") best regards [[alternative HTML version deleted]]

...mple code: ## suppose I have 100 gene (nodes) ## --------------------------------------------------------------------------- graph <- set.vertex.attribute(graph, "color", value=c(rep(c('green','red'),50))) graph <- set.vertex.attribute(graph, "name", value=genelist) tkplot(graph) ---------------------------------------------------------------------------- The 'color' attribute does work, the nodes are red and green, but the 'name' attribute doesn't work, I still have the numeric id on each node (0-99). Can anyone tell me how to solve this...

Hallo, how can I store a variable as a tab-delimited txt-file? I crated a variable with the following commands: > fit12<-lmFit(qrg[,1:2]) > t12<-toptable(fit12,adjust="fdr",number=25,genelist=qrg$genes[,1]) > t12 ID logFC t P.Value adj.P.Val B 522 PLAU_OP -6.836144 -8.420414 5.589416e-05 0.01212520 2.054965 1555 CD44_WIZ -6.569622 -8.227938 6.510169e-05 0.01212520 1.944046 767 CD44_WIZ -8.164317 -8.201678 6.648556e-05 0.01212520 1.928622 123...

...ontrast.matrix) fit2 <- eBayes(fit2) #### top list topTable(fit2, coef=1, adjust="BH", number=20, sort.by="M") library(hgu133plus2.db) u<-mget(row.names(fit2),hgu133plus2SYMBOL) How can I produce a topTable result with according gene names, somehow I do not understand the genelist argument? Next, I would like to produce a standard clustering of the "fold changes" observed within (averaged) contrasts 1 (three - control) and 2 (six - control) and a heatmap presentation of the results. How to extract for example all fold-changes of those genes with a p-value<0.001...