Computational Methods for Single-Cell Data Analysis

Quality Control of Single-cell RNA-seq.- Normalization for Single-cell RNA-seq Data Analysis.- Analysis of Technical and Biological Variability in Single-cell RNA Sequencing.- Identification of Cell Types from Single-cell Transcriptomic Data.- Rare Cell Type Detection.- scMCA- A Tool Defines Cell Types in Mouse Based on Single-cell Digital Expression.- Differential Pathway Analysis.- Differential Pathway Analysis.- Estimating Differentiation Potency of Single Cells using Single Cell Entropy (SCENT).- Inference of Gene Co-expression Networks from Single-Cell RNA-sequencing Data.- Single-cell Allele-specific Gene Expression Analysis.- Using BRIE to Detect and Analyse Splicing Isoforms in scRNA-seq Data.- Preprocessing and Computational Analysis of Single-cell Epigenomic Datasets.- Experimental and Computational Approaches for Single-cell Enhancer Perturbation Assay.- Antigen Receptor Sequence Reconstruction and Clonality Inference from scRNA-seq Data.- A Hidden Markov Random Field Modelfor Detecting Domain Organizations from Spatial Transcriptomic Data.