Computational Methods for Single-Cell Data Analysis

1. Quality Control of Single-cell RNA-seq Peng Jiang

2. Normalization for Single-cell RNA-seq Data Analysis

Rhonda Bacher

3. Analysis of Technical and Biological Variability in Single-cell RNA Sequencing

Beomseok Kim, Eunmin Lee, and Jong Kyoung Kim

4. Identification of Cell Types from Single-cell Transcriptomic Data

Karthik Shekhar and Vilas Menon

5. Rare Cell Type Detection

Lan Jiang

6. scMCA- A Tool Defines Cell Types in Mouse Based on Single-cell Digital Expression

Huiyu Sun, Yincong Zhou, Lijiang Fei, Haide Chen, and Guoji Guo

7. Differential Pathway Analysis

Jean Fan

8. Differential Pathway Analysis

Jean Fan

9. Estimating Differentiation Potency of Single Cells using Single Cell Entropy (SCENT)

Weiyan Chen and Andrew E Teschendorff

10. Inference of Gene Co-expression Networks from Single-Cell RNA-sequencing Data

Alicia T. Lamere and Jun Li

11. Single-cell Allele-specific Gene Expression Analysis

Meichen Dong andYuchao Jiang

12. Using BRIE to Detect and Analyse Splicing Isoforms in scRNA-seq Data

Yuanhua Huang and Guido Sanguinetti

13. Preprocessing and Computational Analysis of Single-cell Epigenomic Datasets

Caleb Lareau, Divy Kangeyan, and Martin J. Aryee

14. Experimental and Computational Approaches for Single-cell Enhancer Perturbation Assay

Shiqi Xie and Gary C. Hon

15. Antigen Receptor Sequence Reconstruction and Clonality Inference from scRNA-seq Data

Ida Lindeman and Michael J.T. Stubbington

16. A Hidden Markov Random Field Model for Detecting Domain Organizations from Spatial Transcriptomic Data

Qian Zhu