Designing a single cell ATAC-Seq (scATAC-Seq) dataset to benchmark scATAC-Seq analysis methods

Single cell sequencing technology has been widely used for understanding the heterogeneity of complex tissue and for identifying novel cell types or cell states. Previous efforts of single cell profiling are mostly performed by measuring transcriptomes using single cell RNA sequencing (scRNA-seq). scRNA-seq is relatively well developed and around 500 analysis tools are currently available for performing different tasks. In the past five years, assays for profiling the single cell chromatin accessibility landscape have emerged and provide extra information about gene regulation at the epigenetic level. Due to its simplicity and sensitivity, single cell Assays for Transposase-Accessible Chromatin using sequencing (scATAC-seq) is widely used to obtain chromatin accessibility. This data will be used to comprehensively evaluate scATAC-seq data analysis tools and gaps in analysis workflows together with publicly available bulk ATAC-Seq and scATAC-seq data using optimised universal evaluation metrics. Our experiment utilized the 5 human lung adenocarcinoma cell lines H2228, H1975, A549, H838 and HCC827. For the single cell designs, the five cell lines were mixed equally and processed by 10X Chromium.