Computational Methods for scRNA-seq Analysis at Cell Level

The remarkable progress in single-cell RNA sequencing (scRNA-seq) in recent years has led to the heat of great development of computational methods and tools for scRNA-seq data analysis. They have seen wide applications in data preprocessing, discovering differential expression, cell grouping, and trajectory inference, etc. To summarize and compare these diverse methods and tools, this paper reviews the algorithms and software including the data preprocessing, cell grouping, and trajectory inference for conducting cell-level scRNA-seq studies.