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...

...m751be.rpkm is a dataframe with dim of 751 samples by 35164 variables, 73 phenotypic variables in the furst to 73rd column and 35091 genomic variables or genes in the 74th to 35164th columns. What I need to do is to calculate the residuals for each gene using the simple linear regression model of genelist[i] ~ purity2; The following code is running, it takes long time, but I have an expensive ThinkStation window computer. Can you provide a fast way to do it? Thank you, Ding --------------------------------------------------------------------------------- gem751be.rpkm <-merge(gem751be10, a...

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...