New Paper is out: Benchmarking Computational Methods for Single-Cell Chromatin Data Analysis
We benchmarked 8 scATAC-seq data processing pipelines for their performance in clustering, predicting gene activities, and integrating with scRNA-seq.
Our preprint is now published on Genome Biology! We benchmarked 8 different scATAC-seq data processing pipelines for their performance in clustering cell populations, predicting gene activities, and integrating with scRNA-seq data. We also explored the influence of some parameters. Based on these results, we generated guidelines to better guide user's choice for methods and parameters. external page Check our paper if you want to know how to better analyze your scATAC-seq data! external page