similar to: NA microarray for kmeans clustering

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 chr1 12 17 6 + gene4 chr1 20 25 6 + gene5

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

Hi, Try this: lines1<- readLines(textConnection("gene1 or1|1234 or3|56 or4|793 gene4 or2|347 gene5 or3|23 or7|123456789")) lines2<-readLines(textConnection(">or1|1234 ATCGGATTCAGG >or2|347 GAACCTATCGGGGGGGGAATTTATATATTTTA >or3|56 ATCGGAGATATAACCAATC >or3|23 AAAATTAACAAGAGAATAGACAAAAAAA >or4|793 ATCTCTCTCCTCTCTCTCTAAAAA >or7|123456789

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

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 chr1 12 17 6 + gene4 chr1 20 25 6 + gene5

Hi Everyone, I am trying to find a way to do this in excel to tell me which genes are the most differentially expressed. Sorry, i couldn't find excel forum section in nabble. However, if it is in R it is fine. This is a microarray data, and it has been normalized. According to Dov Stekel in Microarray, i will need to calculate log ratio (control-treatment). Once you have the log ratio,

>Date: Thu, 6 Mar 2008 06:46:07 -0800 (PST) >From: Keizer_71 <christophe.lo@gmail.com> >Subject: [R] Statistical Questions: finding differentially expressed >genes >To: r-help@r-project.org >Message-ID: <15873163.post@talk.nabble.com> >Content-Type: text/plain; charset=us-ascii >Hi Everyone, >I am trying to find a way to do this in excel to tell me which

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]]

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

Hi, I''m using heatmap.2 to cluster my data, using the centroid method for clustering and the maximum method for calculating the distance matrix: library("gplots") library("RColorBrewer") test <- matrix(c(0.96, 0.07, 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)

Hi r-users,   I would like to use Kolmogorov smirnov test but in my observed data(xobs) there are ties.  I got the warning message.  My question is can I do something about it?   ks.test(xobs, xsyn)           Two-sample Kolmogorov-Smirnov test data:  xobs and xsyn D = 0.0502, p-value = 0.924 alternative hypothesis: two-sided Warning message: In ks.test(xobs, xsyn) : cannot compute correct

Hi R-users, I would like to find the goodness of fit using Chi-suare test for my data below: xobs=observed data, xtwe=predicted data using tweedie, xgam=predicted data using gamma > xobs <- c(223,46,12,5,7,17) > xtwe <- c(217.33,39,14,18.33,6.67,14.67) > xgam <- c(224.67,37.33,12.33,15.33,5.33,15) > chisq.test(xobs, xtwe = xtwe, rescale.p = TRUE) Error in chisq.test(xobs,

Hi Everybody I use R2.8.0 on Mac OS X. I set up LyX 1.6.1 to use Sweave today. I can compile the test file I found on CRAN ( http://cran.r-project.org/contrib/extra/lyx/) without a problem and the output looks very nice. In the test file the following R code is used. <<myFirstChunkInLyX>>= xObs <- 100; xMean <- 10; xVar <- 9 x <- rnorm(n=xObs, mean=xMean, sd=sqrt(xVar))

Full_Name: Nuno Monteiro Version: 2.3.1 OS: Windows XP HE Submission from: (NULL) (84.9.38.207) I'm using the FEAR library to perform Data Envelopment analysis with a 36,000 obs dataset. The function dea is working fine but then when I try to use the boot.sw98 to come up with some sensitivity analysis I get the following error:

Hi all, I am trying to run the mice package (for multiple imputation) on a data frame that is 5174 x 100. When I run mice(frame), I get the following response: Error in solve.default(t(xobs) %*% xobs) : Lapack routine dgesv: system is exactly singular and execution stops. I'm no expert at matrix algebra, so if someone could explain this to me and what I can do to get around it,

Hi list, I have a question about using *read.table()* to read in a txt file. Basically, it consists of 16346 rows, 6 columns (no header). The code I used is: exprSet <- read.table('process_all4_GSA2.txt', row.names = 1,header =FALSE) and I got an error message: > exprSet <- read.table('process_all4_GSA2.txt', row.names = 1,header =FALSE) Error in

Starting with data from a microarray experiment and I would like to analyse the influence of two factors (age, treatment) on gene expression. Looking through the r-help archives and the web I tried the following: I put my data in a dataframe similar to this one: > example.df <- as.data.frame(matrix(data=runif(32,100,1000), nrow=4, ncol=4)) > example.df <-

Dear R users, I am using the MICE package. Specifically, at some point in my code I have imp2=mice(PoptotalMICE,imputationMethod="logreg2") And R returns... iter imp variable 1 1 MICEYError in logitreg(xobs, yobs, intercept=F) : couldn't find function "ms" I have been looking for this ms function on the web, hoping it was just a matter of downloading a

https://bugzilla.mindrot.org/show_bug.cgi?id=2646 Bug ID: 2646 Summary: zombie processes when using privilege separation Product: Portable OpenSSH Version: 7.2p2 Hardware: ix86 OS: Linux Status: NEW Severity: minor Priority: P5 Component: sshd Assignee: unassigned-bugs at

Hi all, I'm a beginner user of R. I am stuck at what I thought was a very obvious problem, but surprisingly, I havent found any solution on the forum or online till now. My problem is simple. I have a file which has entries like the following: #ID Value1 List_of_values ID1 0.342 0.01,1.2,0,0.323,0.67 ID2 0.010 0.987,0.056,1.3,1.5,0.4