Single-cell metabolic profiling reveals subgroups of primary human hepatocytes with heterogeneous responses to drug challenge.

Background: Xenobiotics are primarily metabolized by hepatocytes in the liver, and primary human hepatocytes are the gold standard model for the assessment of drug efficacy, safety, and toxicity in the early phases of drug development. Recent advances in single-cell genomics demonstrate liver zonation and ploidy as main drivers of cellular heterogeneity. However, little is known about the impact of hepatocyte specialization on liver function upon metabolic challenge, including hepatic metabolism, detoxification, and protein synthesis.

epiAneufinder identifies copy number alterations from single-cell ATAC-seq data.

Single-cell open chromatin profiling via scATAC-seq has become a mainstream measurement of open chromatin in single-cells. Here we present epiAneufinder, an algorithm that exploits the read count information from scATAC-seq data to extract genome-wide copy number alterations (CNAs) for individual cells, allowing the study of CNA heterogeneity present in a sample at the single-cell level. Using different cancer scATAC-seq datasets, we show that epiAneufinder can identify intratumor clonal heterogeneity in populations of single cells based on their CNA profiles.

EpiScanpy: integrated single-cell epigenomic analysis.

EpiScanpy is a toolkit for the analysis of single-cell epigenomic data, namely single-cell DNA methylation and single-cell ATAC-seq data. To address the modality specific challenges from epigenomics data, epiScanpy quantifies the epigenome using multiple feature space constructions and builds a nearest neighbour graph using epigenomic distance between cells. EpiScanpy makes the many existing scRNA-seq workflows from scanpy available to large-scale single-cell data from other -omics modalities, including methods for common clustering, dimension reduction, cell type identification and trajectory learning techniques, as well as an atlas integration tool for scATAC-seq datasets.