search for: gene3

...through the posts but couldn't find a solution to this. I'd be really grateful if someone could help, I'd like to convert a data file of mutual information that is formatted as a matrix:             TF1    TF2    TF3    TF200... Gene1    0.0    0.2    0.2 Gene2    1.4    0.0    2.8 Gene3    0.3    0.6    1.7 Gene6000.... To a list: Gene1    TF1    0.0 Gene1    TF2    0.2    Gene1    TF3    0.2 Gene2    TF1    1.4 Gene2    TF2    0.0 Gene2    TF3    2.8 Gene3    TF1    0.3 Gene3    TF2    0.6 Gene3    TF3    1.7 Gene6000...TF200...etc The matrix is ~6000X200 in size, Adam...

hi, folks: i need to transpose the following data: gene tissue patient1 patient2 patient3..... --------------------------------------------- gene1 breast 10 100 1 gene2 breast 20 200 4 gene3 breast 30 50 5 gene4 breast 40 400 9 ................................ to the following format: patientID gene1 gene2 gene3 gene4............ ------------------------------------------- 1 10 20 30 40 2...

Hi all, I have been struggling with this problem for a few days. I have a data table like this: gene rpkm1 diff1 rpkm2 diff2 gene1 23 50 13 120 gene2 111 220 827 1200 gene3 75 998 71 910 And I want to re-format it so that, for each gene, I have a 2x2 contingency table, such as: gene rpkm diff gene1 23 50 gene1 13 120 gene2 111 220 gene2 827 1200 gene3 75 998 gene3 71 910 I have found one post with the same problem (http://r.789695.n4.nabble....

Hey guys, can anyone help? i have a sample table: >table <- structure(c(4, 7, 0.2, 3, .1, 7, 222, 3, 10, 5, 11, 8, 8, 10, 7), .Dim = c(5L, 3L), .Dimnames = list(c("gene1", "gene2", "gene3", "gene4", "gene5"), c("codon1", "codon2", "codon3"))) >table codon1 codon2 codon3 gene1 4.0 7 11 gene2 7.0 222 8 gene3 0.2 3 8 gene4 3.0 10 10 gene5 0.1 5 7 i want to p...

...h of genes ( nearly ~50000) from the whole genome, which read in genomic ranges A range(gene) can be seem as an observation has three columns chromosome, start and end, like that seqnames start end width strand gene1 chr1 1 5 5 + gene2 chr1 10 15 6 + gene3 chr1 12 17 6 + gene4 chr1 20 25 6 + gene5 chr1 30 40 11 + I just wondering is there an efficient way to find *overlapped, upstream and downstream genes for each gene in the granges* For example, assuming all_genes_gr is a ~50000 genes genomic ra...

Hello all! I have the following problem with the %in% command: 1) I have a data frame that consists of functions (rows) and genes (columns). The whole has been loaded with the "read.delim" command because of gene-duplications between the different rows. 2) Now, there is another data frame that contains all the genes (only the genes and without duplicates) from all the functions of

Dear all, Once again I need your help ; I fond a way to do what I want but I am sure there is a better way.. maybe you can help me. I have a matrix, for example mat.tot : > mat.tot ID Desc M1 M2 1 1 gene1 0.5 0.2 2 2 gene2 -0.4 -0.1 3 3 gene3 1.0 1.2 4 4 gene1 0.6 0.3 5 5 gene2 -0.3 0.0 and I want to merge line 1 with line 4, and line 2 with line 5 because this is the same gene. I can do that with the "merge" function but I need to make 2 "virtual" matrices, like this : > ind<-duplicated(mat.tot$Desc) &gt...

...h of genes ( nearly ~50000) from the whole genome, which read in genomic ranges A range(gene) can be seem as an observation has three columns chromosome, start and end, like that seqnames start end width strand gene1 chr1 1 5 5 + gene2 chr1 10 15 6 + gene3 chr1 12 17 6 + gene4 chr1 20 25 6 + gene5 chr1 30 40 11 + I just wondering is there an efficient way to find overlapped, upstream and downstream genes for each gene in the granges For example, assuming all_genes_gr is a ~50000 genes genomic rang...

....07, 0.97, 0.98, 0.50, 0.28, 0.29, 0.77, 0.08, 0.96, 0.51, 0.51, 0.14, 0.19, 0.41, 0.51), ncol=4, byrow=TRUE) colnames(test) <- c("Exp1","Exp2","Exp3","Exp4") rownames(test) <- c("Gene1","Gene2","Gene3", "Gene4") test <- as.table(test) mat = data.matrix(test) heatmap.2(mat, dendrogram="row", Rowv=TRUE, Colv=FALSE, distfun = function(x) dist(x,method = ''maximum''), hclustfun = function(x) hclust(x,method = ''centroid''), xla...

Hey guys, Can anyone help? I did a correspondance analysis and made a plot. I also have a specific list of nodes that i want to find in my plot and want to either color the nodes that appear in my list differently, or put some kind of border around that group of nodes... Would anyone know how to do this? Also, would this post be more relevant here or in the bioconductor forum? -- View this

Hey guys, if i do a correspondance analysis, e.g.: table <- structure(c(4, 7, 0.2, 3, .1, 7, 222, 3, 10, 5, 11, 8, 8, 10, 7), .Dim = c(5L, 3L), .Dimnames = list(c("gene1", "gene2", "gene3", "gene4", "gene5"), c("codon1", "codon2", "codon3"))) Library(ca) plot(ca(table)) is there a way that i can see the "second principal axis" of this analysis? Aoife [[alternative HTML version deleted]]

...I define outMat as object names I want to output to (does this make sense? how else #can I define sequential numbered output?) #numVec is numbers I use in the loop head(Counts) AN1 AN2 AN3 AN4 var GENE1 99 0 6 0 2360 GENE2 183 136 137 160 496 GENE3 301 199 233 187 1856 outMat<-paste("NewCounts", 1:5, sep="_") #names of numVec<-c(100,200,500,1000,1500) cutGenes<-function(x) { for (i in 1:5) { keep<- Counts$var<numVec[i] #gives logical vector keep<-Counts[keep=="TRUE",] #apply l...

hi, everyone: i have a question on the reshape function. i have the following dataset : gene tissue patient1 patient2 patient3............. _________________________________________________ gene1 breast 10 20 50 gene2 breast 20 40 60 gene3 breast 100 200 300 which i hope to convert to the following format: gene patientID value gene1 ----------------------------- gene1 1 10 10 gene1 2 20 20 gene1 3 50 100 gene2 1 20 10 gene2 2 40 20 gene2 3 60 100...

I have 2 files containing data analysed by 2 different methods. I would like to find out which genes appear in both analyses. Can someone show me how to do this? _________________________________________________________________ [[trailing spam removed]] [[alternative HTML version deleted]]

...enes to be differentially expressed. The book did not explained how log ratio will help me determine the significant value. GeneID treatment control treatment control treatment control Gene1 2.1 1 2 2.2 1.1 0.7 2.7 Gene2 1.5 1.4 1.7 2.2 1.3 1.2 Gene3 1.4 1.7 1.8 2.7 1.6 1.5 Gene4 2.2 2.4 2.1 2.3 2.1 1.9 Gene5 2.6 3.4 2.1 1.3 2.6 2.9 Objective: find genes who are differentially epxressed. -- View this message in context: http://www.nabble.com/Statistical-Questions%3A-finding-di...

...y expressed. >The book did not explained how log ratio will help me determine the >significant value. >GeneID treatment control treatment control treatment control >Gene1 2.1 1 2 2.2 1.1 0.7 2.7 >Gene2 1.5 1.4 1.7 2.2 1.3 1.2 >Gene3 1.4 1.7 1.8 2.7 1.6 1.5 >Gene4 2.2 2.4 2.1 2.3 2.1 1.9 >Gene5 2.6 3.4 2.1 1.3 2.6 2.9 >Objective: find genes who are differentially epxressed. I'm not sure what you are asking, but to find whether one of your genes...

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:

...playing around with grid, and a number of other packages for graphing I have data of the following type (much larger of course, and in this case is named "Medoid4"). The first column defines the x-axis, while as each other column is individual y-axes in different plots gene1 gene2 gene3 4 -0.74 -0.63 -0.12 8 3.2 0.3 0.98 12 0.35 0.59 0.22 14 0.22 0.62 -0.2 and I'm graphing simple line plots using the following commands. par(mfrow=c(5,2), mai=c(0.7,0.3,0.2,0.2), omi=c(0.5,0.5,0.5,0.5)) for(i in 2:ncol(Medoid4)){ plot(Medoid4[,1], Medoid4[,i], type="b", col=&quo...

...consists of 22277 rows, 72 columns. > exprSet <- read.table('70mel_GSA.txt', row.names = 1,header =FALSE) > dim(exprSet) [1] 22277 71 > exprSet[1:4,1:4] V2 V3 V4 V5 GENE1 DDR1 10.215229 8.546666 9.207030 GENE2 RFC2 8.028489 8.175520 9.090902 GENE3 HSPA6 4.633769 4.822625 5.125172 GENE4 PAX8 6.121433 6.396281 6.000987 The two txt files are of similar format. The only difference so far I can tell is that the second file is of more rows and columns. Other than that, they are basically the same. But I don't know what is the issue with th...

...lt;-read.table("test.txt",header=FALSE,skip=1,row.names=1) V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 gene1 0.14 0.07 -0.58 -0.56 -0.25 -0.17 1.02 0.98 0.18 0.28 0.23 0.37 gene2 NA NA NA NA NA NA NA NA NA NA NA NA gene3 0.00 0.28 -0.01 0.29 0.14 NA 0.23 NA 0.08 0.00 -0.47 -0.57 gene4 -0.58 -1.22 -0.43 -0.23 NA -0.36 0.30 0.28 0.30 0.41 0.33 -0.08 gene5 -1.51 -1.36 -1.64 -1.89 -1.32 -0.38 -0.14 -0.32 0.39 0.58 0.19 -0.40 gene6 -0.50 -0.60 -0.42 0.41 0.32 NA NA NA -0.69 0.29 0.12 0....