similar to: Message for R-help mailing list

Dear R-experts, My problem is how to handle a 10GB data file containing genotype data. The file is in a particular format (Illumina final report) and needs to be altered and merged with phenotype data for further analysis. PERL seems to be an frequently used solution for this type of work, however I am inclined to think it should be doable with R. How do I open a text-file, line by line,

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

Hi, I am new to R. and even though I've made my code to run and do what it needs to . It is taking forever and I can't use it like this. I was wondering if you could help me find ways to fix the code to run faster. Here are my codes.. the data set is a bunch of 0s and 1s in a data.frame. What I am doing is this. I pick a column and make up a new column Y with values associated with that

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:

Hi R-help folks, I have been doing some single SNP association work using snpMatrix. This works well, but produces a lot of false positives, because of population structure in my data. I would like to correct the p-values (which snpMatrix gives me) for population structure, possibly using principle component analysis (PCA). My data is complicated, so here's a simple example of what

Dear R users, Could you help my with the following problem? I want to repeat a glm analysis with 2 independent variables for all 900 variables (snps) in my data set. So, I want to check whether snp1 has a different effect on my outcome variable in patients and controls(phenotype). And repeat that for snp2 to snp900. Is there an easy way to get a summary of the data, e.g. a list of P values of all

Hi, My query is regarding permutation test and reshuffling of genotype/phenotype data I have been using the haplo.stats package of R. for haplotype analysis and I would like to perform an analysis which I'm requesting your advice. I have a data set of individuals genotyped for 12 SNP and a dichotomous phenotype. At first, I have tested each of those SNP independently in order to bypass

Hello R Forum users, I was hoping someone could help me with the following problem. Consider the following "toy" dataset: Accession SNP_CRY2 SNP_FLC Phenotype 1 NA A 0.783143079 2 BQ A 0.881714811 3 BQ A 0.886619488 4 AQ B 0.416893034 5 AQ B 0.621392903 6 AS B 0.031719125 7 AS NA 0.652375037 "Accession"

Hi, I'm looking for an efficient code that will enable me to reshuffle data (phenotype) for certain number of individuals and creating a loop that will randomly simulate it for 10000 times *(permutation)*. I also need to find how I keep the information (p value for each SNP) gathered for all the 10000 iterations. My data set looks like this (n=500): Individual # Phenotype SNP1 SNP2

Hello, I have data in a dataframe with 139104 rows which is multiple of 96x1449. i have a phenotype file which contains the phenotype information for the 96 samples. the snp name is repeated 1449X96 samples. I haveto merge the two dataframes based on sid and sen. this is how my two dataframes look like dat<-data.frame(snpname=rep(letters[1:12],12),sid=rep(1:12,each=12),

Hi: I use lm (linear model) to analyze 47 variables , 8 responses So I use loop to finish it . I want the program to show the results that P-value is less than 0.05. How can I cite the P-valus from lm result ? Ping The code: #using LM to model general fati for (j in 48:52) { for (i in 3:46){ gen.fat<-y_x[,j] gen.fat<-as.numeric(gen.fat) snp_marker<-y_x[,i] x<-colnames(y_x)

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

Dear experts, I am trying to perform an association using snpStats. I have a snp matrix called 'plink' which contains my genotype data (as a list of $genotypes, $map, $fam), and a phenotype data frame which contains the outcomes (outcome1, outcome2,...) I would like to associate with the genotype. My question is, how do I loop through the outcomes? This type of data seems different from

Hi, I cant understand where I am going wrong.Below is my code.I would really appreciate your help. Thanks. > genfile<-read.table("c:/tina/phd/bs871/hw/genfile.txt",skip=1) > > #read in SNP data > snp.dat <- as.matrix(genfile) > snp.name <- scan("c:/tina/phd/bs871/hw/genfile.txt",nline=1,what="character") Read 100 items

Bottom Line Up Front: How does one reshape genetic data from long to wide? I currently have a lot of data. About 180 individuals (some probands/patients, some parents, rare siblings) and SNP data from 6000 loci on each. The standard formats seem to be something along the lines of Famid, pid, fatid, motid, affected, sex, locus1Allele1, locus1Allele2, locus2Allele1, locus2Allele2, etc In other

Dear Sir/Madam, Since a few day now I try to use the command "polygenic" from the GenAbel package. However, I keep bumping up against an error message: "Error in polygenic(Testo, kin = kinship, data = data1) : dimension of outcome and kinship.matrix do not match". My data exists of 1240 individuals with 74 markers. It mainly consists of small families (2 or more brothers,

Hello all, I'm having difficulty with setting up a mixed model using lme in the nlme package. To summarize my study, I am testing for effects of ornamentation on foraging behavior of wolf spiders. I tested spiders at two different ages (penultimate vs. mature) and of two different phenotypes (one species tested lacks ornamentation throughout life [non-ornamented males] while the other

Currently 4.12.3 is scheduled for 19 May: https://wiki.samba.org/index.php/Release_Planning_for_Samba_4.12#Samba_4.12.3 As Ralph has a patch and you have confirmed it odds are pretty good this will be in there. Andrew Bartlett On Sun, 2020-05-10 at 00:01 +0200, pavlos wrote: > Hi, > did you already decide if, and - if yes - how and when the patch will be embedded into the mainstream?

On Sat, 2020-05-09 at 18:33 +0200, pavlos via samba wrote: > > Ralph, good news! > > Applying the patch into the original source code of the 'open.c' file > removes the observed misbehavior. > So yes, you've touched and addressed the root-cause of the problem > on my side. MANY THANKS! > Double checked that from two WIn7 stations - x86 and x64, also from my

Hello to all speex developers, I have question regarding payload length of narrowband speex in RTP. I were watching tcpdump of the xlite softphone and have found that it uses weird payload length namely 75 Bytes I went through various source and without success. To be clear: For 8000Hz sample in 20 ms that is 160 samples per frame. This makes 50 frames per sec. modes bit-rate 8 kbit/s