search for: snp2

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 > GT[1,,] <- pmin(SNP1,SNP2) > dim(GT) NULL # why?????????????????????????????????????? > GT[2,,] <- pmax(SNP1,SNP2) Error in GT[2, , ] <- pmax(SNP1, SNP2) : inco...

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")) > x id snp1 snp2 snp3 1 1 A G G 2 2 G G G 3 3 G G A Now I want to know that snp2 in monomorphic (the same value for the column) and after I...

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 snp...

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 reshape the dataset in such a way that the individuals get 2 observation...

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 V2 V3 1 snp1 snp2 s...

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...

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...

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 SN...

...AA=2) aa Aa AA case 2 3 0 control 2 2 0 So I should not use this one or if I am using it, then I need to see 0 0 in to AA column which I don't see when I use the table command in R. snpmat category SNP1 SNP2 SNP3 .... SNPN case 1 0 2 1 case 0 1 1 2 case 1 2 2 0 control 0 1 0 1 control...

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 ID4 _ _ _ _ ID5 CC GG CC AA ID6 CC GG CC AA ID7 CC...

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 C A Dataset 2: Individual SNP1 SNP3 SNP5 SNP6 SNP7 4 A T T G C 5 T A A G G 6 A A T C G I want Dataset1 to have only columns that are al...

...evaluate it and write it back into a textfile in a different position; Phenotypeinfo.txt (contains phenotype information) Before.txt (contains genotypeinformation -see below-) SNP;1-305,000 ID:1-900 allele.A alleleB After.txt (the required format) ID:1-250 phenotype SNP1.allelA SNP1.alleleB SNP2.Allele.A SNP2.allele.B etc I have been looking at ?read.table/scan/readline/SQL-light but have not resolved it. Should I refer to PERL or can this be tackled? I am using a windows machine with R 2.6.0 Any help would be highly appreciated, Many Thanks, Marco

...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 is the "SNP1,SNP2" are not working in this place, because it's not a right format to use the SNP information stored in the GenABEL library. Someone said I could first import the GenABEL format genetic data to the format used by "genetics" library...

...e) 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 SNP3 SNP4 SNP5 SNP6 SNP7 SNP8 SNP9 SNP10 SNP11 SNP12 1 0 T T G G A C G T A A T C 2 1 A T C G A C G T A G T C Many thanks, Jonathan [[alternative HTML version deleted]]

...asy to add these rows, but for 'gwaa at gtdata', I think I need to create SNP data as '0 0 0 0 0.....' for all the dummy parents first. I am using the function 'convert.snp.ped', so I need a 'pedfile' of this format: #ped id fa mo sex trait snp1.allele1 snp1.allele2 snp2.allele1 snp2.allele2 ...# 1 1 0 0 1 2 0 0 0 0 ... 1 2 0 0 1 0 0 0 0 0 ... 1 3 0 0 2 1 0 0 0 0 ... . . 100 101 0 0 2 1 0 0 0 0 ... If we use the 1M microarray, usually, after QC, there will be ~800 thousands SNPs, so this file is really huge. I created this matrix in R, and then try to export this...

...r 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 900 variables? I tried something with a loop: for (i in 1:length(data)) { print (summary (glm (outcome~data[[i]]*phenotype, data=data))) } # This works, but gives 900 written summaries for (i in 1:leng...

...snp.data = matrix( c(0,1,0,-1,-1,1,1,-1,0,1,1,0,0,1,0,-1,-1,NA,0,-1,0,0,1,0), nrow=3, dimnames = list( c("bob", "frita", "trudy"), c("snp1", "snp2", "snp3", "snp4", "snp5","snp6", "snp7", "snp8") ) ) # phenotype data - resistant or susceptible to zombie infection phenotype.data = matrix( c("bob", "frita", "trudy&q...