Differential expression analysis was performed with R package Deseq2 (version 1.22.2) for RNA-seq data and R package Limma (version 3.38.3) for proteomics data. In all datasets, black and white cases were allowed retaining the 0 for both parental and resistant cells. For RNA-seq data, only genes having a total sample count > 10 were retained. Volcano plots were generated using R package EnhancedVolcano, principal component analysis and sample correlation analyses were performed with plotPCA function of DeSeq2 R package and pheatmap R package (version 1.0.12). Finally, the R-package ggvenn was used to count the genes significantly upregulated in common among the cell lines and between RNA-seq and proteomics datasets.
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