similar to: Predicted Cox survival curves - factor coding problems...

The combination of survfit, coxph, and factors is getting confused. It is not smart enough to match a new data frame that contains a numeric for sitenew to a fit that contained that variable as a factor. (Perhaps it should be smart enough to at least die gracefully -- but it's not). The simple solution is to not use factors. site1 <- 1*(coxsnps$sitenew==1) site2 <-

Hello I have two data frames, SNP4 and SNP1: > head(SNP4) Animal Marker Y 3213 194073197 P1001 0.021088 1295 194073197 P1002 0.021088 915 194073197 P1004 0.021088 2833 194073197 P1005 0.021088 1487 194073197 P1006 0.021088 1885 194073197 P1007 0.021088 > head(SNP1) Animal Marker x 3213 194073197 P1001 2 1295 194073197 P1002 1 915 194073197

Why does the assignment of a 3178x93 object to another 3178x93 object remove the dimension attribute? > GT <- array(dim = c(6,nrow(InData),ncol(InSNPs))) > dim(GT) [1] 6 3178 93 > SNP1 <- InSNPs[InData[,"C1"],] > dim(SNP1) [1] 3178 93 > SNP2 <- InSNPs[InData[,"C2"],] > dim(SNP2) [1] 3178 93 > dim(pmin(SNP1,SNP2)) [1] 3178 93

Dear R helpers I have a table and i need to make new table table1: sire snp1 snp2 snp3 snp4 snp5 snp6 snp7 snp8 snp9 snp10 snp11 snp12 snp13 snp14 snp15 8877 -1 -1 -1 -1 0 0 -1 -1 -1 0 1 1 1 -1 -1 7765 1 1 1 0 0 0 -1 1 1 1 0 0 0 1 0 8766 1 1 -1 0 -1 -1 0 -1 0 -1 -1 -1 0 1 0 6756 0 1 0 -1 1 -1 -1 0 0 0 0 -1 0 1 1 5644 -1 0 1 -1 0 0 0 0 -1 -1 0 0 0 0 1 I have table2 sire

Hi, I've got a quite tricky question. I have a txt file, named 'temp.txt', as the following: snp1 snp2 snp3 AA 00 00 GG GG 00 00 AA 00 I want to read the file into R. 1) when I use 'read.table' without 'header=T' option, > temp <- read.table('temp.txt') # I got > temp V1

Hi ihave one table that look like SNP1 SNP2 SNP3 SNP4 SNP5 SIRE1 1 -1 -1 1 -1 SIRE2 1 -1 1 1 1 SIRE3 -1 -1 1 1 0 SIRE4 -1 1 1 0 1 SIRE5 -1 1 -1 -1 1 SIRE6 0 0 0 1 -1 SIRE7 -1 0 -1 1 1 SIRE8 1 -1 NA 0 NA SIRE9 -1 1 1 -1 -1 SIRE10 1 1 1 1 1 table 2 only one line SNP1 SNP2 SNP3 SNP4 SNP5 SIRE100 -1 -1 1

Hi, I have a large dataset on which I would like to do the following: x<-data.frame(id=c(1,2,3), snp1=c("AA","GG", "AG"),snp2=c("GG","AG","GG"),snp3=c("GG","AG","AA")) > x id snp1 snp2 snp3 1 1 AA GG GG 2 2 GG AG AG 3 3 AG GG AA And then

Does anyone use the R library GenABEL? I am using it to calculate SNP interactions. I have a list of 100 SNPs, I need to look at the interaction between each of two SNPs among the list. my question is how to perform this in GenABEL. I want to use the "lm" function, but don't know how to use the SNP information. for example: result <- (lm(y~SNP1+SNP2+SNP1*SNP2)) the problem here

Hello all, I hope some of you can come to my rescue, yet again. I have two genetic datasets, and I want one of the datasets to have only the columns that are in common with the other dataset. Here is a toy example (my real datasets have hundreds of columns): Dataset 1: Individual SNP1 SNP2 SNP3 SNP4 SNP5 1 A G T C A 2 T C A G T 3 A C T

Hi, I have a question about the data handling. I have a dataset as following: ID snp1 snp2 snp3 1001 0/0 1/1 1/1 1002 2/2 3/3 1/1 1003 4/4 3/3 2/2 I want to convert the dataset to the following format: ID snp1 snp2 snp3 1001 00 AA AA 1002 GG

Martin, Actually domain doesn't crash, but it state got changed to pause, till the snapshot action got complete. Its a time consuming process. so here is my requirement. I want to take snapshot of a Running Domain on every 3 hours,( at a later point of time It should be possible to revert to the actual domain state when I took the snapshot), I'm using libvirt APIs python bindings, there

Hi ihave one table that look like SNP1 SNP2 SNP3 SNP4 SNP5 SIRE1 1 -1 -1 1 -1 SIRE2 1 -1 1 1 1 SIRE3 -1 -1 1 1 0 SIRE4 -1 1 1 0 1 SIRE5 -1 1 -1 -1 1 SIRE6 0 0 0 1 -1 SIRE7 -1 0 -1 1 1 SIRE8 1 -1 NA 0 NA SIRE9 -1 1 1 -1 -1 SIRE10 1 1 1 1 1 table 2 only one line SNP1 SNP2 SNP3 SNP4 SNP5 SIRE100 -1 -1 1 1 -1 I need to male

Hi, I'm using libvirt(1.0.0) with python, for managing virtual machines.. but while taking multiple snapshot domain is crashing... Snapshot XML ------------------------- <domainsnapshot> <name>snp1</name> <creationTime></creationTime> <description>Description</description> <state></state> <domain>

Hi Readers, I have a question. I have a large dataset and want to throw away columns that have the same value in the column itself and I want to know which column this was. For example > x<-data.frame(id=c(1,2,3), snp1=c("A","G", "G"),snp2=c("G","G","G"),snp3=c("G","G","A"))

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,

I have a few questions about GenABEL, gwaa data. 1) is there a universal way that most GenABEL people use to add more individuals into a 'gwaa' data? For example, I have a 'gwaa' data, but I need to add some dummy parents, for 'gwaa at phdata', it's easy to add these rows, but for 'gwaa at gtdata', I think I need to create SNP data as '0 0 0 0 0.....'

On Tue, Jun 03, 2014 at 04:02:21PM +0530, Sijo Jose wrote: >Hi, >I'm using libvirt(1.0.0) with python, for managing virtual machines.. >but while taking multiple snapshot domain is crashing... > >Snapshot XML >------------------------- > ><domainsnapshot> > <name>snp1</name> > <creationTime></creationTime> >

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

I'm new to R (previously used SAS primarily) and I have a genetics data frame consisting of genotypes for each of 300+ subjects (ID1, ID2, ID3, ...) at 3000+ genetic locations (SNP1, SNP2, SNP3...). A small subset of the data is shown below: SNP_ID SNP1 SNP2 SNP3 SNP4 Maj_Allele C G C A Min_Allele T A T G ID1 CC GG CT AA ID2 CC GG CC AA ID3 CC GG nc AA

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