similar to: Multiple versions of data in a package

Hi I am having problems compiling R on a Solaris 10 opteron box we have on trial. checking for Fortran libraries of g77... -L/usr/ccs/lib -L/usr/lib - L/usr/local/lib -L/usr/local/lib/gcc-lib/i386-pc-solaris2.10/3.3.2 - L/usr/ccs/bin -L/usr/local/lib/gcc-lib/i386-pc- solaris2.10/3.3.2/../../.. -lfrtbegin -lg2c -lm -lgcc_s -lfrtbegin: - lg2c: checking how to get verbose linking output from

Hi All, I am having some problems with my R compile and matrix.c My config setings are:- setenv CC "cc -xarch=amd64" setenv F77 "f95 -xarch=amd64" setenv CXX "CC -xarch=amd64" setenv CFLAGS "-xO5 -xlibmil -dalign" setenv FFLAGS "-xO5 -xlibmil -dalign" setenv CXXFLAGS "-xO5 -xlibmil -dalign" setenv SHLIB_CXXLDFLAGS -lCstd setenv LDFLAGS

Hi, I am trying to compile R-2.1.1 on Solaris10, with the Studio10 compilers. When I try to compile 64bit with CFLAGS="-xarch=amd64" export CFLAGS I get a configure failure on checking for rl_callback_read_char in -lreadline... no checking for history_truncate_file... no configure: error: --with-readline=yes (default) and headers/libs are not available unset CFLAGS and its fine

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

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

Hi, Following my earlier posts about having problems performing a PCA, I have worked out what the problem is. The problem lies within the PLINK to gds conversion. It seems as though the SNPs are imported as "samples" and in turn, the samples are recognised as SNPs: >snpsgdsSummary("chr2L") Some values of snp.position are invalid (should be > 0)! Some values of

Hello, I'm (eventually) attempting a singular value decomposition of a 3200 x 527829 matrix in R version 2.10.1. The script is as follows: ###---------Begin Script here-------### library(Matrix) snps <- 527829 ## Number of SNPs N <- 3200 ## Sample size y <- rnorm(N, 100,1) ## simulated phenotype system.time( ## read in matrix

If I run an analysis which generates statistical tests on many SNPs I would naturally want to get more details on the most significant SNPs. Directly from within R one can get the information by loading RSNPer (from Bioconductor) and simply issuing a command SNPinfo(2073285). Unfortunately, the command cannot handle a vector and therefore only wants to do one at a time. I tried the lapply and

Dear all, After struggling for some time with *apply() and eva() without success, I decided to ask for help. I have 3 lists labeled with, each contains 3 different interpolation functions with identical names: > names(missgp0) [1] "spl.1mb" "spl.2mb" "spl.5mb" > > names(missgp1) [1] "spl.1mb" "spl.2mb" "spl.5mb" > >

Hi All, I have a problem with weighted logistic regression. I have a number of SNPs and a case/control scenario, but not all genotypes are as "guaranteed" as others, so I am using weights to downsample the importance of individuals whose genotype has been heavily "inferred". My data is quite big, but with a dummy example: > status <- c(1,1,1,0,0) > SNPs <-

Hi, I am using the sim1000G R package to simulate data for case/control study. I can not figure out how to manipulate this code to be able to generate 10% or 50% causal SNPs in R. This is whole code provided as example on GitHub: library(sim1000G) vcf_file = "region-chr4-357-ANK2.vcf.gz" #nvariants = 442, ss=1000 vcf = readVCF( vcf_file, maxNumberOfVariants = 442 ,min_maf =

Hi Mr Tierney, I have noticed an error message from R 1.12.x's CMD check for a while (apparently prof Ripley completely rewrote CMD check in R 1.12+) e.g.: http://bioconductor.org/checkResults/2.7/bioc-LATEST/snpMatrix/lamb2-checksrc.html ---------------- * checking R code for possible problems ... NOTE Warning: non-unique value when setting 'row.names': ?new? Error in

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

Dear useRs, First off, sorry about the long post. Figured it's better to give context to get good answers (I hope!). Some time ago I wrote an R function that will get all pairwise interactions of variables in a data frame. This worked fine at the time, but now a colleague would like me to do this with a much larger dataset. They don't know how many variables they are going to have in the

Dear All, Does anybody have experience with R package pbatR (http://cran.r-project.org/web/packages/pbatR/index.html)? I am trying to use it to analyze the family-based case-control data, but the package totally doesn?t work on my computer. I contacted the authors of the package, but I haven?t heard anything from them. Following the package manual, I tried the simple example as below:

This will probably seem very simple to experienced R programmers: I am doing a snp association analysis and am at the model-fitting stage. I am using the Stats package's "drop1" with the following code: ##geno is the dataset ## the dependent variable (casectrln) is dichotomous and coded 0,1 ## rs743572_2 is one of the snps (which is coded 0,1,2 for the 3 genotypes)

Hi all, We are using two methods to identify SNPs. One is based on resequencing the genome and aligning the reads to the sequenced genome to identify SNPs (data available for 44 individuals). Another is based on SNP array with selected loci (30000 loci, 870 individuals). I want to compare the results from the resequencing based minor allele frequency and Array based minor allele frequency.

Hello, I did a pca with over 200000 snps for 340 observations (ids). If I plot the eigenvectors (called rotation in prcomp) 2,3 and 4 (e.g. plot (rotation[,2]) I see a strange "column" in my data (see attachment). I suggest it is an artefact (but of what?). Suggestion: I used prcomp this way: prcomp (mat), where mat is a matrix with the column means already substracted followed by a

Hello all, I am trying to make a genome association plot for p-values related to SNPs and was fortunate to find that R contains a package that produces Manhattan plots which is what's preferred for my current project. The function mhtplot() is found in the 'gap' package which I installed in R 2.11.1 on Windows. I thought I'd test out the function first with the examples they

I a using plink on a large SNP dataset with a .map and .ped file. I want to get some sort of file say a list of all the SNPs that plink is saying that I have. ANyideas on how to do this? -- Thanks, Jim. [[alternative HTML version deleted]]