Additional file 1: Figure S1. of Seed-effect modeling improves the consistency of genome-wide loss-of-function screens and identifies synthetic lethal vulnerabilities in cancer cells
Year: 2017
Type: article
Abstract: Correlation based on shESs in high data quality cell lines. Figure S2. Examples of seed essentiality (seedES) calculations in an artificial dataset. Figure S3. Rank correlation (ρ) for high data quality cell lines based on shES and seedES over all shRNA family sizes. Figure S4. Reproducibility of the seed essentiality scores with increasing shRNA family size of seed sequences. As shown in Fig. 3, we added the gray trace indicating the correlation based on the average of correlations from all positions. Figure S5. Heatmap of average Spearman correlation of seedES scores with increasing family size, between the matched cell lines, by considering different positions along the shRNA molecule as the seed sequence. Figure S6. As shown in Fig. 5, the number of overlapping SL partners of major cancer driver genes observed in both datasets, before and after cleaning, where the cleaning was based on removal of shRNAs with a high tendency for off-target seed effects (defined by SPS and TA properties of seed sequences; Fig. 4). Figure S7. GARP-based geneES for PKN3 and HMX3 before and after cleaning in PIK3CA mutant and wild-type (WT) cell lines, separately for the Achilles 2.4 and COLT-cancer datasets. Figure S8. Density plots of geneES scores for all the genes and gold-standard constitutive core essential (CCE) genes. Gene-specific phenotypes were calculated based on gespeR and GARP scores in both Achilles and COLT-Cancer datasets, respectively. Figure S9. A stepwise procedure for cleaning genome-wide shRNA datasets. Figure S10. Baseline reproducibility between the Achilles 2.4 and BFG genome-wide shRNA screens. Figure S11. Reproducibility of Achilles 2.4 and BFG genome-wide screens at the level of shRNAs, on-target genes, and off-target seeds. Figure S12. Reproducibility of seed essentiality scores with increasing shRNA family size of seed sequences in additional datasets. Figure S13. Reproducibility of Achilles 2.4 and BFG datasets after accounting for seed sequence properties. (DOCX 1588 kb)
Source: Figshare
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7136064019