lva.internal {AllelicImbalance} | R Documentation |
make an almlof regression for arrays (internal function)
lva.internal(x, ...) ## S4 method for signature 'array' lva.internal(x, grp, element = 3, type = "lm", subject = NULL, covariates = matrix(), ...)
x |
regionSummary array phased for maternal allele |
... |
arguments to forward to internal functions |
grp |
group 1-3 (1 for 0:0, 2 for 1:0 or 0:1, and 3 for 1:1) |
element |
which column in x contains the values to use with lm. |
type |
which column in x contains the values to use with lm. |
subject |
which samples belongs to the same individual |
covariates |
add data.frame with covariates (only integers and numeric) |
internal method that takes one array with results from regionSummary and one matrix with group information for each risk SNP (based on phase). Input and output objects can change format slightly in future.
Jesper R. Gadin, Lasse Folkersen
data(ASEset) a <- ASEset # Add phase set.seed(1) p1 <- matrix(sample(c(1,0),replace=TRUE, size=nrow(a)*ncol(a)),nrow=nrow(a), ncol(a)) p2 <- matrix(sample(c(1,0),replace=TRUE, size=nrow(a)*ncol(a)),nrow=nrow(a), ncol(a)) p <- matrix(paste(p1,sample(c("|","|","/"), size=nrow(a)*ncol(a), replace=TRUE), p2, sep=""), nrow=nrow(a), ncol(a)) phase(a) <- p #add alternative allele information mcols(a)[["alt"]] <- inferAltAllele(a) # in this example two overlapping subsets of snps in the ASEset defines the region region <- split(granges(a)[c(1,2,2,3)], c(1,1,2,2)) rs <- regionSummary(a, region, return.class="array", return.meta=FALSE) # use (change to generated riskSNP phase later) phs <- array(c(phase(a,return.class="array")[1,,c(1, 2)], phase(a,return.class="array")[2,,c(1, 2)]), dim=c(20,2,2)) grp <- matrix(2, nrow=dim(phs)[1], ncol=dim(phs)[2]) grp[(phs[,,1] == 0) & (phs[,,2] == 0)] <- 1 grp[(phs[,,1] == 1) & (phs[,,2] == 1)] <- 3 #only use mean.fr at the moment, which is col 3 lva.internal(x=assays(rs)[["rs1"]],grp=grp, element=3)