VincentizeRTs

RTbins <- function(x) {
  # Don't vincentize if too few cells
  if (length(x)<10) {
    binsRT = c(NA, NA, NA, NA, NA, NA)
    return(binsRT)
  }

  # Find the percentiles of the array; these are your bounds
  counti=0
  critpe <- c()
  for(p in seq(0, 1, by=0.2)) {
    counti = counti + 1
    critpe <- c(critpe, quantile(x, p))
  }

  RTb = vector('list', 5)

  # Now sort into bins (fastest to slowest)
  for(i in 1:length(x)) {
    ifelse( (x[i] >= critpe[1] & x[i] < critpe[2] ) , RTb[1] <- c(RTb[1],x[i]),

           ifelse( (x[i] >= critpe[2] & x[i] < critpe[3] ), RTb[2] <- c(RTb[2],x[i]),

                  ifelse( (x[i] >= critpe[3] & x[i] < critpe[4] ), RTb[3] <- c(RTb[3],x[i]),

                         ifelse( (x[i] >= critpe[4] & x[i] < critpe[5] ), RTb[4] <- c(RTb[4],x[i]),

                                 ifelse( (x[i] >= critpe[5] & x[i] < critpe[6] ), RTb[5] <- c(RTb[5],x[i]), next

    )))))
  }

  binsRT <- c(mean(x, na.rm=TRUE))
  binsRT <- c(binsRT, mean(RTb[1]))
  binsRT <- c(binsRT, mean(RTb[2]))
  binsRT <- c(binsRT, mean(RTb[3]))
  binsRT <- c(binsRT, mean(RTb[4]))
  binsRT <- c(binsRT, mean(RTb[5]))


  return(binsRT)
}