A multiplex single-cell RNA-Seq pharmacotranscriptomics pipeline for drug discovery

We developed a single-cell transcriptomics pipeline for high-throughput pharmacotranscriptomic screening. We explored the transcriptional landscape of three HGSOC models (JHOS2, a representative cell line; PDC2 and PDC3, two patient-derived samples) after treating their cells for 24 hours with 45 drugs representing 13 distinct classes of mechanism of action. Our work establishes a new precision oncology framework for the study of molecular mechanisms activated by a broad array of drug responses in cancer.
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├── 3D UMAPs/ → Interactive 3D UMAPs of cells treated with the 45 drugs used for multiplexed scRNA-seq. Related to Figure 4.
Coordinates: x = UMAP 1; y = UMAP 2; z = UMAP 3.
Legend: green = PDC1; blue = PDC2; red = JHOS2.
│ ├── DMSO_3D_UMAP_Dini.et.al.html → 3D UMAP of untreated cells.
│ └── drug_3D_UMAP_Dini.et.al.html → 3D UMAP of cells treated with (drug).
├── QC_plots/ → Diagnostic plots. Related to Figures 2–4.
│ ├── model_QC_violin_plot_2023.pdf → Violin plots of the QC metrics used to filter the data.
│ ├── model_col_HTO or model_row_HTO before and after filt → Heatmaps of the row or column HTO expression in each cell.
│ └── model_counts_histogram_2023.pdf → Histogram of the distribution of the total counts per cell after filtering for high-quality cells.
├── scRNAseq/ → scRNA-seq data. Related to Figures 2–4.
│ ├── AllData_subsampled_DGE_edgeR.csv.gz → Differential gene expression analyses results between treated and untreated cells via pseudobulk of aggregate subsamples, for each of the three models. Related to Figure 3.
│ └── All_vs_all_RNAclusters_DEG_signif.txt → Differential gene expression analysis results (p.adj < 0.05) of FindAllMarkers for the Leiden/RNA clusters.
├── PDCs.transcript.counts.tsv → Bulk RNA-seq count data for PDCs 1–3 processed by Kallisto. Related to Figure S6.
└── PDCs.transcript.TPM.tsv → Bulk RNA-seq TPM data for PDCs 1–3 processed by Kallisto. Related to Figure S6.