聚类分析

单细胞转录组数据无监督聚类中的挑战: https://www.dazhuanlan.com/2020/02/23/5e51e58af1ed9/?__cf_chl_jschl_tk__=c536c7dc12efb4abbd6617ba3dadc2b84b081f36-1590602116-0-AQYsGAw6mLdfMxq7tgc2V69HKy26eo4h9OXhwufwZ2Tc1Z9iHPVoHiPjEf4Y9tycRcM5-81KlzsgLWjCCQg367s18fp3BKv3WYSl8IS-6ElNc-3eLNq0DLnyKE2GVDa7SSi-evVCMHrLUsaHD-zTr55d7K7JzFh0iCZy-eo7Qzs0dFqObuncKPtVFgaJX8B8DYfqMkon3CypyChyI20snvn_lG7AwdJ2fQnpCjuOBMOGau5woLnsDV6oHYND-CMCH4aWs2eVs1hssZhc_4oVkK4VpKmdn3QOMD9T8_v88_j4MPl5RxnFP9OYsfO4l3rDyQ

单细胞去除聚类的离群点: https://zhuanlan.zhihu.com/p/108747990

单细胞转录组学习笔记-8-聚类算法之PCA与tSNE: https://www.jianshu.com/p/ebd1c6fa79d3

R语言实现UMAP降维模型: https://cloud.tencent.com/developer/article/1476996

How to Use t-SNE Effectively: https://distill.pub/2016/misread-tsne/

数据降维与可视化——t-SNE: https://blog.csdn.net/hustqb/article/details/78144384

UMAP: https://evvail.com/2019/08/18/78.html