> for(chr in chrs) {	# For each chromosome,
> RTc = subset(RT, CHR == chr)	# Create subset of timing values in the chromosome
> RSc = subset(RefSeq, CHR == chr)	# Create subset of RefSeq genes in the chromosome
> cat(“Current chromosome: “, chr, “\n”)	# Output current chromosome to console
> lspan = 300000/(max(RTc$POSITION)-min(RTc$POSITION))	# Set smoothing span
> smLym1 = loess(RT$mLymphR1 ~ RT$POSITION, span = lspan)	# Smooth dataset 1
> smLym2 = loess(RT$mLymphR2 ~ RT$POSITION, span = lspan)	# Smooth dataset 2
> smLym3 = loess(RT$mLymphAve ~ RT$POSITION, span = lspan)	# Smooth dataset 3
> Lym1 = predict(smLym1, RSc$TSS)	# Predict (interpolate) values at transcription start sites
> Lym2 = predict(smLym2, RSc$TSS)	# Predict values for dataset 2
> Lym3 = predict(smLym3, RSc$TSS)	# Predict values for dataset 3
> ChrSm = data.frame(CHR=chr,POSITION= RSc$TSS, Lym1, Lym2, Lym3)
> AllSm = rbind(AllSm, ChrSm)	# Combine information for all experiments/chromosomes
> }	# End for loop