Figure 2

Performance comparison of counting strategies on simulated L1-enriched data. Three replicates of ChIP-seq (50 bp single-end reads) data enrichment at L1 elements on chromosome 19 were simulated using the hidden Markov model (HMM) in Additional file 1: Figure S2. The expected average log2CPM for the simulation was computed using the repetitive element counts computed from the true read coordinates. The average log2CPM read abundances, computed by EdgeR from RepEnrich estimated count values using total, unique, and fractional count methods were compared to the expected true abundance. The solid line indicates y = x, values falling on the line are identical between the estimated average log2CPM and expected average log2CPM. The repetitive element subfamilies are colored according to class with small RNA repeats including scRNA, rRNA, snRNA, and tRNA classes. A) Comparison of the estimated abundance from the unique count method, which only sums reads that can be assigned uniquely to a single subfamily of repetitive elements, versus the true abundance. B) Comparison of the estimated abundance from the total count method, which sums the reads assigned to each repetitive element subfamily and allows for multiple counting of reads, versus the true abundance. C) Comparison of the estimated abundance from the fractional count method, which sums the reads that fall into each individual repetitive element subfamily once, but adds a fraction for reads mapping to more than one subfamily (1/# of repetitive element sub-families aligned), versus the true abundance. D) Multidimensional scaling (MDS) plot of the Euclidean distances between the average log2CPM values for the unique, total, and fractional count estimates of RepEnrich and the expected average log2CPM values. The fractional count average log2CPM estimate was closest to the true abundance.