Figure 4
From: High-throughput translational profiling with riboPLATE-seq
Principal Component Analyses (PCA) of riboPLATE-seq data in TS-543 cells. (a) riboPLATE-seq ribosome association (RA, riboPLATE-seq-PLATE-seq), (b) difference in RA between each sample and the average across DMSO-treated samples (lfcRA), normalized by variance-stabilizing transform (VST) in DESeq2 (R v4.0.5). For both plots, the domain of the PCA was restricted to genes with significant changes in RA reported by DESeq2 for any drug treatment relative to DMSO, (FDR < 0.05, 1813 genes total; detailed in Fig. 4c). Drug treatments elicit changes consistent enough to yield clustering behavior among samples treated with the same drug in both analyses, as well as co-clustering of related drug treatments (e.g. BKM120, PP242, and AZD8055). Separation is also apparent between combination treatments and their constituent, individual drugs in each plot. (c) Significant effects of each drug determined in riboPLATE-seq by DESeq2 (Benjamini–Hochberg adjusted false discovery rate (FDR) < 0.05). Genes determined significantly up- or downregulated in ribosome association (RA) are tallied for each drug and combination treatment.
