生信单细胞测序

单细胞数据分析流程和验证实验

2022-02-04  本文已影响0人  Hayley笔记
1. 分析流程
Basic algorithms
  • Expression quantification and quality control
  • Normalization (CPM/TPM + logarithm)
  • Batch effect correction for integrating multiple datasets
  • Feature selection (only keeping highly variable genes)
  • Principle Component Analysis (acceleration + denoise)
  • Non-linear dimensional reduction for visualization (tSNE/UMAP)
  • Unsupervised clustering (K-means/community detection)
  • Differential expression (one-vs-rest)
  • Annotate clusters based on marker genes
Additional algorithms
  • Supervised annotation
  • Trajectory inference for continuous cell states
  • RNA velocity analysis
  • Cell-cell interaction analysis
  • Deconvolution analysis for bulk-data
  • Integrated analysis with other techniques (scATAC-seq, CITE-seq, spatial-seq, TCR/BCR-seq)
2. 验证实验

参考:加这些单细胞测序验证实验,高分文章稳了!

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