similar to: snpStats imputed SNP probabilities

Hi everyone, I am doing 5 years mortality predictive index score with survival analysis using a Cox proportional hazard model where I have a continous predictive variable and a right censored response which is the mortality, and the individuals were followed a maximum of 7 years. I'd like to asses the discrimination ability of survival analysis Cox model by computing a ROC curve and area

FYI. There is a Thai vignette - and it went a lot further doing some Thai text processing in R, than the earlier Chinese/Tibetan/LiangshanYi/Arabic vignette, which was in reality just Chinese + Cairo graphics. Managed to cross-compile an R package for Mac OS X from Linux; and it seems to be working. See screenshots below. I'd be interested to know if there are less obvious bugs; however

Hi, Anybody knows a function that can fit haplotype data to a Cox model. I've been searching it in the web without succeed. I use "haplo.stats" package, but unfortunatelly it's not possible to analyse survival data, amb I right?. Thanks in advance. Isaac Subirana (isubirana@imim.es) [[alternative HTML version deleted]]

Hi, Does anybody know how to obtain the same information as the SPSS command "DISPLAY DICTIONARY". I know the read.spss function in the package foreign, but it doesn't give either the missing values defined by the user under SPSS or the format variables (for example if they are dates or not). Thanks in advance. Isaac Subirana (isubirana@imim.es) [[alternative HTML

Hi R-users, When I import a data base from SPSS with some variable with a name of more than 8 characters (which is possible in version 12 or later of SPSS software) I find that the name of these variables have been truncated to 8 characters. I used the 'read.spss' function from the 'foreign' package. Is there a function in R that solves this 'length variable names'

Hello, I would like to plot specific SNPs with their exact locations on a chromosome. Based on my genotyping results I would like to separate these SNPs in three different categories: 1, 2 and 3 and use different colours to represent these categories. The script below generates the sample data. I can plot these with the image function using the following: val <- 1:3 samp <- sample(val,

Hello, I have indicators for the present of absent of a snps in columns and the categorey (case control column). I would like to extract ONLY the tables and the indices (SNPS) that give me 2 x 3 tables. Some gives 2x 2 tables when one of the allelle is missing. The data look like the matrix snpmat below: so the first snp should give me the following table: (aa=0, Aa=1 and AA=2) aa

The windows replacement is R-library-grDevices-libs-winCairo_20150122.zip in http://sourceforge.net/projects/outmodedbonsai/files/R/ The cairo replacements are just two bundles, windows or OS X - containing replacements for R 2.15.3, 3.0.3 and 3.1.2. You just extract the relevant one for your R version. The windows builds of R packages snpStats x.x.x.8 and snpMatrix 1.19.0.20 were done with

Dear all, I generated a dataset with 500 unrelated individuals and 10 biallelic SNPs. From this dataset,I would like to create data with 5% missingness on genotype information at random and also data with 5% genotyping error. Can someone help me with how I can do it. [[alternative HTML version deleted]]

Hi, Does anybody know how to perform a Cox model analysis for right truncated data? All my data is right truncated, since I only have patients who entered in a hospital for a particular desease, and I would like to modelate the age at hospital entrance as the response variable. Thanks in advance. Isaac Subirana. isubirana@imim.es -------- La informació continguda en aquest missatge i

R.framework-Versions-Resources-library-grDevices-libs-cairo_20150120.tgz in http://sourceforge.net/projects/outmodedbonsai/files/R/ are dropped in replacement to the cairo.so's in the official R binaries (2.15.3, 3.0.3, 3.1.2). updated to cairo-1.12.18 and freetype-2.5.4. The official R binaries' were built with early freetype 2.4.x and cairo 1.11(?) and had a number of issues with some

Hi there, I checked google for aov. usually one uses summary to see whether the p-value is small. but I want to put aov in my script. how can I get the p-value, (0.1115, 0.6665, 0.6665 in the following example)? thanks YU > datafilename="http://personality-project.org/r/datasets/R.appendix2.data" > data.example2=read.table(datafilename,header=T) > aov.ex2 =

Hello, I'm new to R and have been following many guides including the two-way anova (http://www.personality-project.org/r/r.anova.html). Using that walkthrough including the supplied data I do str(data.ex2) and receive the appropriate types of data as follows: > str(data.ex2) 'data.frame': 16 obs. of 4 variables: $ Observation: int 1 2 3 4 5 6 7 8 9 10 ... $ Gender :

Dear All, Thank you kindly for such detailed replies. I was looking to overlay data using algorithms so that i am able to tell which genes are differentially expressed due to changes in copy number. I did a pubmed search and found only 7 literature pieces all of which use in-house algorithms. I am yet to explore Gviz since it wouldn't work on R 2.14, would try it after upgrading to R 2.15.

Hi, The program below work very well. (snps = c('rs621782_G', 'rs8087639_G', 'rs8094221_T', 'rs7227515_A', 'rs537202_C')) Selec = todos[ , colnames(todos) %in% snps] head(Selec) But, I have a data set with 1.000 columns and I need extract 70 to use (like snps in command above). This 70 snps are in a file. So I create a file to extract them with

Hi there, I have a question regarding a data set that looks like the following: 8 repeated measurements for 3 dosage levels. However, the measurements for each dosage levels are taken on a different group of subjects. example: subject time dosage measure 11         1          1          154 11         2          1          150 :          :           :             : 11        

Hi, I am trying to reconcile anova table in R (summary(lm)) with individual t.test. datafilename="http://personality-project.org/R/datasets/R.appendix1.data" data.ex1=read.table(datafilename,header=T) #read the data into a table summary(lm(Alertness~Dosage,data=data.ex1)) gives: Call: lm(formula = Alertness ~ Dosage, data = data.ex1) Residuals:    Min     1Q Median     3Q    Max

Dear R developers: I am a PHD candidate student in the school of public health of Peking University and my major is genetic epidemiology. I am learning the FAM-MDR algorithm, which is used to detect the gene-gene and gene-environment interactions in the data of pedigree. The codes were written by Tom Cattaert of the University of Liege. The algorithms and the sample datasets are available at

I have a solution (actually a few) to this problem, but none are computationally efficient enough to be useful. I'm hoping someone can enlighten me to a better solution. I have data frame of chromosome/position pairs (along with other data for the location). For each pair I need to determine if it is with in a given data frame of ranges. I need to keep only the pairs that are within any of

Dear R-devel, I am writing for help on how I should include parallel sets of data in my package. Brief summary: I am new to using data within packages. I want a user to be able to specify one of two alternative versions of within-package datasets to use, and I want to load just that one. I have a solution that works, but it doesn't seem as simple as it should be from a user's