1. Evaluating CRISPR negative selection screens.
Evaluating CRISPR negative selection screens. The fold‐change distributions of gRNA targeting reference essential and nonessential genes in Shalem et al (2013) are similar to those shown by shRNA hairpins (see Fig 1) and enable the application of the Bayes Factor approach. Published results from Shalem et al (2013), evaluated against CCE‐test and NE‐test. Dashed line shows that Bayes Factor approach more accurately captures essential genes in the A375 screen, the only screen for which raw data is available. Whole‐screen results from Wang et al (Wang et al, 2013), evaluated against the same sets. NE‐test genes are underrepresented in the Wang et al gRNA library, which gives the appearance of an artificial boost in precision when compared to the Shalem et al (2013) results. Comparing shRNA to CRISPR. Genes are rank‐ordered by expression (gray curve, left axis) and binned. For four shRNA screens in pancreatic cancer cell lines withheld from the original analysis (red), the fraction of essential genes (by BF, no prior) in each bin (± s.d., right axis) is plotted against the mean expression of all genes in the bin. Genes with trace expression (log2(FPKM) < −2) are not essential and can therefore estimate background error rate (dashed line). Comparing CRISPR results demonstrates that, for the one dataset available, CRISPR can yield a similar number of essential genes at ˜10‐fold lower FPR (green, BF ≥ 20, 660 genes), or double the number of essential genes at similar error rates (blue, BF ≥ 10, 1,319 genes).
Traver Hart et al. Mol Syst Biol 2014;10:733
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