PRJDB6952 Multi-omics characterization of drug perturbations in lung cancer cell lines In this study, we constructed comprehensive transcriptome and epigenome catalogues of responses to various well-annotated compounds in 23 lung cancer cell lines. We selected 95 compounds including approved receptor tyrosine kinase inhibitors and epigenetic targeting drugs. To obtain profiles of transcriptome and epigenome changes by drug administration, we depeloved a high-throughtput sequencing platform of RNA-seq and ATAC-seq. We generated 3,240 RNA-seq and 3,393 ATAC-seq datasets from cells treated with the compounds. The data comprise two kinds of datasets: the datasets obtained from five cell lines treated with four concentrations of 23 selected compounds at three time points (24, 48, 72h) (dataset-1); and the datasets obtained from 23 cell lines treated with one concentration of 95 compounds for 24h (dataset-2). Furthermore, we integrated multi-omics information based on transcriptome modules and investigated whether the drugs could control transcriptome and epigenome patterns of the modules and finally regulate phenotypic responses such as cellular survival of lung cancers. Here we demonstrated multi-omics characterization of drug perturbations and module-based regulation of lung cancer cells. Multi-omics characterization of drug perturbations in lung cancer cell lines bioproject PRJDB6952 PRJDB6952 true In this study, we constructed comprehensive transcriptome and epigenome catalogues of responses to various well-annotated compounds in 23 lung cancer cell lines. We selected 95 compounds including approved receptor tyrosine kinase inhibitors and epigenetic targeting drugs. To obtain profiles of transcriptome and epigenome changes by drug administration, we depeloved a high-throughtput sequencing platform of RNA-seq and ATAC-seq. We generated 3,240 RNA-seq and 3,393 ATAC-seq datasets from cells treated with the compounds. The data comprise two kinds of datasets: the datasets obtained from five cell lines treated with four concentrations of 23 selected compounds at three time points (24, 48, 72h) (dataset-1); and the datasets obtained from 23 cell lines treated with one concentration of 95 compounds for 24h (dataset-2). Furthermore, we integrated multi-omics information based on transcriptome modules and investigated whether the drugs could control transcriptome and epigenome patterns of the modules and finally regulate phenotypic responses such as cellular survival of lung cancers. Here we demonstrated multi-omics characterization of drug perturbations and module-based regulation of lung cancer cells.