similar to: reordering huge data file

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

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, 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

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

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 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 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

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, 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

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 SNP5 SIRE100 -1 -1 1

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

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

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

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

Hello, I need some help with the simulatedSNPs function from scrime package. I am trying to simulate some genotype of a case/control disease locus. The allele frequence are cases/controls Sample cases controls 2000 .5 .10 1500 .6 .40 In each of the row, i need to simulate 100 snp and calculate the pvalue ##############Download Scrime

Hi, I am conducting an association analysis of genotype and a phenotype such as cholesterol level as an outcome and the genotype as a regressor using multiple linear regression. There are 3 possibilities for the genotype AA, AG, GG. There are 5 people with the AA genotype, 100 with the AG genotype and 900 with the GG genotype. I coded GG genotype as 1, AG as 2 and AA as 3 and the p-value for the

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

Dear All, The following code extracts from NCBI very nice output for ONE allele of a SNP (often the allele with the second largest frequency - usually termed the minor allele). It gives an average minor allele frequency from all NCBI sources (which is what I want, except I'd like the addition of data for all the other alleles of one SNP) plus a table of minor allele frequencies from each

Hello R-help community, I have another question about filtering datasets. Please consider the following "toy" data matrix example, called "x" for simplicity. There are 20 different individuals ("ID"), with information about the alleles (A,T, G, C) at six different loci ("Locus1" - "Locus6") for each of these 20 individuals. At any single locus