makePWM <- function(pwm, alphabet="DNA"){
if (is.data.frame(pwm)) pwm <- as.matrix(pwm)
if (!is.matrix(pwm)) stop("pwm must be a matrix or a dataframe")
if (!alphabet %in% c("DNA","AA"))
stop("alphabet must be either DNA or AA")
if (alphabet == "DNA" & nrow(pwm) != 4){
stop("PWM for DNA motifs must have 4 rows")
}else if (alphabet == "AA" && nrow(pwm) != 21){
stop("PWM for amino acid motifs must have 21 rows")
}
if (any(abs(1 - apply(pwm,2,sum)) > 0.01)){
print(apply(pwm,2,sum))
warning("Columns of PWM must add up to 1.0")
}
width <- ncol(pwm)
colnames(pwm) <- 1:width
rownames(pwm) <- c("A","C","G","T")
cons <- pwm2cons(pwm)
ic <- pwm2ic(pwm)
new("pwm", pwm=pwm, consensus=cons, ic=ic, width=width, alphabet=alphabet)
}
## get information content profile from PWM
pwm2ic<-function(pwm) {
npos<-ncol(pwm)
ic<-numeric(length=npos)
for (i in 1:npos) {
ic[i] <- 2 + sum(sapply(pwm[, i], function(x) {
if (x > 0) { x*log2(x) } else { 0 }
}))
}
ic
}
## get consensus sequence from PWM
pwm2cons<-function(pwm) {
if (class(pwm)!="matrix") {warning("pwm argument must be of class matrix")}
letters <- c("A", "C", "G", "T")
paste(apply(pwm, 2, function(x){letters[rev(order(x))[1]]}), collapse="")
}
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