similar to: R data Export to Excel

Hello, Thanks everyone for helping me with the previous queries. step 1: Here is the orginal data: short sample ProbeID Sample_1_D Sample_1_C Sample_2_D Sample_2_C 1 224588_at 2.425509867 11.34031409 11.46868531 11.75741478 step 2: i calculate the variance of the sample using this R code x<-1:20000 y<-2:141 data.matrix<-data.matrix(data[,y])#create data.matrix

Hi Everyone, I need some simple help. Here are my codes ##########will give me 10000 probesets#################### data.sub = data.matrix[order(variableprobe,decreasing=TRUE),][1:10000,] dim(data.sub) data_output<-write.table(data.sub, file = "c://data_output.csv", sep = ",", col.names = NA) When i export to excel, it shows me this. This is just a short version. There

Hi Everyone, Thanks for all the help with the previous queries. Here is what i want to do. i have 20000 probesets-->calculate all the variance accross all the probesets-->filter out probesets that are low so now i ended up with only 10000. The 10000 is fine but when i export to excel, it is missing the probeID. Here are my code and examples. #########calculate the variance across the

***********reading in data********** data<-read.table("microarray.txt",header=T, sep="\t") head(data) dim(data) attach(data) ***********creating matrix and calculating variance across probesets******** x<-1:20000 y<-2:141 data.matrix<-data.matrix(data[,y]) variableprobe<-apply(data.matrix[x,],1,var) hist(variableprobe) **************filter out low

Hi Guys, I am having a real hard time trying to figure out for microarry. Here is my code One-Sample t-Test dim(data.sub) [1] 10000 140 ##there are 10000 probesets and 140 columns hist(data.sub) ## Histogram. Identify if the probesets are normal distributed q<-rnorm(10000) ##generate 10000 random, normal distributed values qqplot(data.sub,q)) ##Show the plot of the probeset

Hi, I am using "*Maanova* package" to do anova. I have created *datafile* with probeID as the first column, which is a tab limited text file and also created *designfile*. I have created *readma object* which is named as abf1. >From that readma object, i have to create data object by using *createData*function and also i hav to create model object by using *makemodel* function,

I am trying to use lme to fit a mixed effects model to get the same results as when using the following SAS code: proc mixed; class refseqid probeid probeno end; model expression=end logpgc / ddfm=satterth; random probeno probeid / subject=refseqid type=cs; lsmeans end / diff cl; run; There are 3 genes (refseqid) which is the large grouping factor, with 2 probeids nested within each refseqid,

Hi, I am interested in using the cast function in R to perform some aggregation. I did once manage to get it working, but have now forgotten how I did this. So here is my dilemma. I have several thousands of probes (about 180,000) corresponding to each gene; what I'd like to do is obtain is a frequency count of the various occurrences of each probes for each gene. The data would look

I have a file with a data in columnar format like below: probeID rc_AI104113_at rc_AI178259_f_at rc_AI179134_i_at rc_AI179134_f_at rc_AI104113_at rc_AA819429_f_at How can I rewrite it in the format below: 'rc_AI104113_at', 'rc_AI178259_f_at', 'rc_AI179134_i_at', 'rc_AI179134_f_at', 'rc_AI104113_at', 'rc_AA819429_f_at' Is there any function to do

Hello, I have this in excel Control 543_BU 123_AT 432_CU I want to be able to import to R so that it will read like this c<-c("543_BU","123_AT","432_CU") output: [1] "543_BU" "123_AT" "432_CU" This is just a short version. I have about 200000 rows and i need a simpler way instead of typing each one. thanks -- View this message

Dear R users, I am using the beadarray package. I am trying to upload raw bead-level data using these commands: ######################################################## library(beadarray) datadir <- ("C:/Computer_programs/R/beadarray/cecilia") targets = read.table("targets.txt", sep = "\t", header = TRUE, as.is = TRUE) BLData = readIllumina(arrayNames =NULL,

Hi, I have been using 'read.table' regularly to read tab-delimited text files with data. No problem, until now. Now I have a file that appeared to have read fine, and the data inside looks correct (structure etc), except I only had 15000+ rows out of the expected 24000. Using 'readLines' instead, and breaking up the data by tabs, gives me the expected result. I do not

inputfille snpid indid genotype gvariable probeid gene geneexpression rs1040480 CHB_NA18524 C/T 2 GI_19743926-I PTPRT 5.850586 rs1040480 CHB_NA18526 C/C 1 GI_19743926-I PTPRT 6.028641 rs1040480 CHB_NA18529 C/C 3 GI_19743926-I PTPRT 5.944392 rs1040481 CHB_NA18532 C/C 1 GI_19743926-I PTPRT 5.938578 rs1040481 CHB_NA18537 C/C 2 GI_19743926-I PTPRT 5.874439 rs1040481 CHB_NA18540 C/C 3 GI_19743926-I

I am trying to use lme to fit a mixed effects model to get the same results as when using the following SAS code: proc mixed; class refseqid probeid probeno end; model expression=end logpgc / ddfm=satterth; random probeno probeid / subject=refseqid type=cs; lsmeans end / diff cl; run; There are 3 genes (refseqid) which is the large grouping factor, with 2 probeids nested within each refseqid,

Hi, I am relatively new to R and Bioconductor and am trying to filter the topTable that I generated of differentially expressed genes from my normlized eset file comprised of ~ 40 HG-133A Affy microarrays . I would like to see if particular probesets are represented in this list. Alternatively I would like to generate a topTable of differentially expressed genes using only specified probesets

Hi, I am using "*Maanova* package" to do anova. I have created *datafile* with probeID as the first column, which is a tab limited text file and also created *designfile*. I have created *readma object* which is named as abf1. >From that readma object, i have to create data object by using *createData*function and also i hav to create model object by using *makemodel* function,

Hello: I am trying to work with a couple of microarray data sets, using platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status major 1 minor 8.1 year 2003 month 11 day 21 language R In the shortcut for invoking R I have set

Hi, I have a question concerning the analysis of some affymetrix chips. I downloaded some of the data from GEO GSE11324 (see below). In doing so I'm stuck after I identified the probesets with significant changes. I have problems in assigning probeset specific gene names as well as getting the genomic coordinates. Furthermore I have no clue how to deal with the fact, that most genes have

> dim(data.sub) [1] 10000 140 #####extracting all differentially express genes########## library(multtest) two_side<- (1-pt(abs(data.sub),50))*2 diff<- mt.rawp2adjp(two_side) all_differ<-diff[[1]][37211:10000,] all_differ #####list of differentially expressed genes########## > probe.names<- + all_differ[[2]][all_differ[[1]][,"BY"]<=0.01] Error in

Hi, Am using maanova package for doing anova.But am getting error like this..plz, help me regarding this.. > TGR=read.madata("rmaexpr.dat",designfile="design.dat") Reading one color array. Otherwise change arrayType='twoColor' then read the data again Warning messages: 1: In read.madata("rmaexpr.dat", designfile = "design.dat") : Assume that