Figure 4.

Performance of two confidence estimations. A comparison of two FDR estimations against the real FDR for the two spike-in datasets with low and high number of reads. Empirical FDRs (eFDR) were calculated and plotted (A) for a variety of thresholds by dividing the number of control enriched regions (input1 vs. input2) by the number of chIP enriched regions (chIP vs. input2). The actual FDR was calculated by intersecting each enriched region set with the spike-in key. The q-value FDR estimation (B) is made by calculating binomial p-values for each window and applying the Storey q-value FDR approximation. For each of the spike-in datasets, windows were generated using two different minimum number of reads, either 1 or 10. The latter represents a filtered dataset that improves the q-value estimation at the cost of test sensitivity (see also Figure 2A).

Nix et al. BMC Bioinformatics 2008 9:523   doi:10.1186/1471-2105-9-523
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