> chrs = levels(RT$CHR); str(chrs)	# Create a list of all chromosomes
> AllLoess = NULL	# Initialize a variable to store all loess-smoothed data
> for (chr in chrs) {	# For each chromosome,
> RTl = NULL	# Create a variable to store loess-smoothed values
> RTb = subset(RT, RT$CHR == chr)	# Subset the dataset to a single chromosome
> lspan = 300000/(max(RTb$POSITION)-min(RTb$POSITION))	# Set smoothing span
> cat(“Current chromosome: “, chr, “\n”)	# Output current chromosome to console
> RTla = loess(RTb$ mLymphR1~ RTb$POSITION, span = lspan)	# Smooth dataset 1
> RTlb = loess(RTb$mLymphR2~ RTb$POSITION, span = lspan)	# Smooth dataset 2
> RTlc = loess(RTb$mLymphAve ~ RTb$POSITION, span = lspan)	# Smooth dataset 3
> RTl = data.frame(CHR=RTb$CHR, POSITION=RTb$POSITION, RTla$fitted, RTlb$fitted,	# Combine the datasets for the current chromosome
> AllLoess = rbind(AllLoess, RTl)	# Combine current chromosome with overall dataset
> }	# End for loop
> x = as.data.frame(AllLoess)	# Reformat the smoothed datasets as a data frame