search for: gene

...irst do an imap LIST, i.e, . list "" * If list is not done first, the imap select or status command on the shared mailbox results in a "NO" response with "mailbox doesn't exist" response text. I can provide more information if this is not expected behavior. -gene

Good Afternoon, My name is Gabriel, I'm doing an analysis if there is increase or decrease in dependence on the mutated genes, using 3 or more genes using the fisher exact test.I performed with success an analysis for two genes using fisher.test( ). example of the 2x2 contigency table: Gene A mutated | Gene A normalGene B mutated| 26 | 12-------...

...86_64., and the R versions are 2.4, 2.4 and 2.2, respectively. So, it would seem that this is platform and R version independant. The file that I'm reading contains the upstream regions of the yeast genome, with each upstream region labeled using a FASTA header, i.e.: FASTA header for gene 1 upstream region..... ..... .... FASTA header for gene 2 upstream.... .... The script I use - code below - opens the file, parses for a FASTA header, and then parses the header for the gene name. Once this is done, it reads the following lines which contain the upstream...

I would appreciate please a suggestion on how to do the following : i'm working with a dataframe in R that contains in a specific column multiple gene names, eg : > df.sample.gene[15:20,2:8] Chr Start End Ref Alt Func.refGene Gene.refGene284 chr2 16080996 16080996 C T ncRNA_exonic GACAT3448 chr2 113979920 113979920 C T ncRNA_exonic LINC01191,LOC100499194465 chr2 131279347 131279347 C G ncRNA_exonic...

Hi Bogdan, Messy, and very specific to your problem: df.sample.gene<-read.table( text="Chr Start End Ref Alt Func.refGene Gene.refGene 284 chr2 16080996 16080996 C T ncRNA_exonic GACAT3 448 chr2 113979920 113979920 C T ncRNA_exonic LINC01191,LOC100499194 465 chr2 131279347 131279347 C G ncRNA_exonic LOC440910 525 chr2 223777...

...#> Attaching package: 'dplyr' #> The following objects are masked from 'package:stats': #> #> filter, lag #> The following objects are masked from 'package:base': #> #> intersect, setdiff, setequal, union library(purrr) library(tidyr) df.sample.gene<-read.table( text="Chr Start End Ref Alt Func.refGene Gene.refGene 284 chr2 16080996 16080996 C T ncRNA_exonic GACAT3 448 chr2 113979920 113979920 C T ncRNA_exonic LINC01191,LOC100499194 465 chr2 131279347 131279347 C G ncRNA_exonic LOC440910 525 chr2 2...

...ack" "chr04" "LOC_Os04g01040" 30637 37300 "TE_related" "black" ... I have worked on the following code to do this job using function and loop, but it is not working. If someone help me, I would really appreciate!!! The original data frame is Os.chr4.gene.new. Gene <- Os.chr4.gene.new[, c("if_TE_related")] Genecolor <- function(Gene) { lg <-length(Gene) for(i in 1:lg) { if (Gene == "TE_related") {D1 <- (Gene == "black")} if (Gene == " ") {D1 <- (Gene == "orange")} } Gene.color &...

Hi all, I have a list of genes present in 500 individuals, the individuals are the elements: Genes <- lapply(1:nrow(inds),function(x) sample(1:10000,inds$No_of_Genes,replace=TRUE)) (This was later written to a dataframe as well as kept as the list object: inds2 <- data.frame(inds,Genes=I(Genes))) I also have a vector of...

Hi, First my apologies for a non-working piece of code in a previous submission, I have corrected this error. I'm doing is individual based modelling of a pathogen and it's host. The way I've thought of doing this is with two dataframes, one of the pathogen and it's genes and effector genes, and one of the host and it's resistance genes. During the simulation, these things can be pulled out of the dataframes and operated on, before being stored again in the dataframes. Below is how I've created my dataframe and stored my effector genes. In this model, effe...

Hello R-users, I am currently trying to learn how to use the function gls of the nlme library. I fitted the following model: Generalized least squares fit by REML Model: response ~ array + dye + genes + variety + variety * genes + array * genes + dye * genes Data: data I have 11 arrays, 2 dyes, 2 varieties, 3200 genes, and 2 replications for each. Therefore I should have the corresponding degrees of freedom and number of coe...

X-Original-In-Reply-To: <CAD0Rxe=5uLCWQ+jfj1J6zepDzqx0vAiBREiwiKOih59MKgBDHg at mail.gmail.com> X-Previous: http://www.syslinux.org/archives/2015-January/023070.html On Mon, Jan 05, 2015 at 08:59:57PM -0500, Gene Cumm wrote: > On Sat, Jan 3, 2015 at 1:21 PM, Geert Stappers wrote: > > On Thu, Jan 01, 2015 at 09:48:16AM -0500, Gene Cumm wrote: > > >> I'm planning on doing the master > >> branch (including the one behind the currently broken git daemon at > >> git.zy...

Hello R users, I have gene expression data of two groups of genes (large and small). Gene expression intensities of those genes are classified into 1 to 10 levels. What I want is to make a random set of genes that have the same levels as the small group from large group using sample(). I used smallvec to hold the number of...

Hi BioC user, I have a problem extracting the gene set I would like to work with. Here is I work with my data: normData <- read.delim("normalizedData.txt",sep ="\t") ######### two class unpaired comparison # y must take values 1,2 classes <- c(-1,-2,1,2) #prepere the data for the samr analysis data.x <-as.matrix(norm...

I do have a bunch 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...

Hello: I am a novice R user, but I have been working my way through the manuals / tutorials, ... I have R / Deducer up and running, and know the basics. I want to analyze a microarray (gene expression) dataset. I need to input the data into R as a multidimensional (multi-way) array, something on the order of 15,000 x 3 x 8 x 2 [genes x replicates x time points x treatments] I've Google'd, etc. to find the solution, but I cannot find an answer. I am being led to the idea (...

Hi, I'm heaving difficulties with a dataset containing gene names and positions of those genes. Not such a big problem, but each gene has multiple exons so it's hard to say where de gene starts and where it ends. I want the starting and ending position of each gene in my dataset. Attached is the dataset: http://www.nabble.com/file/p21312449/genlistchrom...

Hi, May be you can try this: dat1New<-? dat1[!(duplicated(dat1$gene)|duplicated(dat1$gene,fromLast=TRUE)),] dat2<-dat1[duplicated(dat1$gene)|duplicated(dat1$gene,fromLast=TRUE),] ?lst1<-split(dat2,dat2$gene) dat3<-unsplit(lapply(lst1,function(x) {x1<- sum(apply(x[,6:32],2,function(y) y[1]>=y[2]));x2<- sum(apply(x[,6:32],2, function(y) y[1]<=y[2...

Thanks for the advice. My question is more on how to do this? Let me use a biology gene analysis example to illustrate: In biology, there are always some house keeping genes which differ little even at pathological conditions. We know that at different batches, there are external factors affect the measurements. For example, overall signal intensity might be different due to lab rea...

...below. Any guidance on if that's possible or not, and what kinds of commands I should be looking into would be very much appreciated. I'm using R 1.9.0 on Windows XP. Thanks! Paul # load libraries library(stats); # working copy of data set1 <- as.matrix(data); set2 <- t(set1); # genes genes.distance <- as.dist(1-cor(set2)); genes.clusters <- hclust(genes.distance); genes.dendrogr <- as.dendrogram(genes.clusters); # samples samples.distance <- as.dist(1-cor(set1)); samples.clusters <- hclust(samples.distance1); samples.dendrogr <- as.dendrogram(samples.cluster...

Hi, all, I am new to R or even to statistics. Not sure if the question has a answer. But I couldn't find a straight forward answer in the help mailing list. I need use MicroArray data to select several diagnostic genes between Normal samples and Tumor samples and use these genes to predict unknow samples. Since the sample size is so small and data doesn't follow normal distribution, I am thinking to use logistic regression instead of Student T test to select genes. To make the problem simpler, I assume each...