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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

Outlook

48. Outlook

Acknowledgements

49. Acknowledgements

Glossary

50. Glossary

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By Lukas Heumos, Anna Schaar, single-cell best practices consortium

© Copyright 2023.

Brought to you by Theislab, with many thanks to the single-cell community as a whole!