单细胞多组学学习资源，内容包含表达谱、染色质可及性、空间转录组、

Single-cell best practices学习资源所有内容如下：

Introduction

• 1. Prior art
• 2. Single-cell RNA sequencing
• 3. Raw data processing
• 4. Analysis frameworks and tools
• 5. Interoperability

Preprocessing and visualization

• 6. Quality Control
• 7. Normalization
• 8. Feature selection
• 9. Dimensionality Reduction

Identifying cellular structure

• 10. Clustering
• 11. Annotation
• 12. Data integration

Inferring trajectories

• 13. Pseudotemporal ordering
• 14. RNA velocity
• 15. Lineage tracing

Dealing with conditions

• 16. Differential gene expression analysis
• 17. Compositional analysis
• 18. Gene set enrichment and pathway analysis
• 19. Perturbation modeling

Modeling mechanisms

• 20. Gene regulatory networks
• 21. Cell-cell communication

Deconvolution

• 22. Bulk deconvolution

Chromatin Accessibility

• 23. Single-cell ATAC sequencing
• 24. Quality Control
• 25. Gene regulatory networks using chromatin accessibility

Spatial omics

• 26. Single-cell data resolved in space
• 27. Neighborhood analysis
• 28. Spatial domains
• 29. Spatially variable genes
• 30. Spatial deconvolution
• 31. Imputation

Surface protein

• 32. Quality control
• 33. Normalization
• 34. Doublet detection
• 35. Dimensionality Reduction
• 36. Batch correction
• 37. Annotation

Adaptive immune receptor repertoire

• 38. Immune Receptor Profiling
• 39. Clonotype analysis
• 43. Specificity analysis
• 44. Integrating AIR and transcriptomics

Multimodal integration

• 45. Paired integration
• 46. Advanced integration

Reproducibility

• 47. Reproducibility