Selected article for: "principal component analysis and uniform manifold"
Author: Minfeng Liao; Yang Liu; Jin Yuan; Yanling Wen; Gang Xu; Juanjuan Zhao; Lin Chen; Jinxiu Li; Xin Wang; Fuxiang Wang; Lei Liu; Shuye Zhang; Zheng Zhang
Title: The landscape of lung bronchoalveolar immune cells in COVID-19 revealed by single-cell RNA sequencing
  • Document date: 2020_2_26
    • ID: 8l1vfsbc_51
    Snippet: The filtered gene-barcode matrix was normalized with LogNormalize methods in Seurat and analyzed by principal component analysis (PCA) using the top 2, 000 most variable genes. Then Uniform Manifold Approximation and Projection (UMAP) was performed on the top 50 principal components for visualizing the cells. Meanwhile, graph-based clustering was performed on the PCA-reduced data for clustering analysis with Seurat v3......
    Document: The filtered gene-barcode matrix was normalized with LogNormalize methods in Seurat and analyzed by principal component analysis (PCA) using the top 2, 000 most variable genes. Then Uniform Manifold Approximation and Projection (UMAP) was performed on the top 50 principal components for visualizing the cells. Meanwhile, graph-based clustering was performed on the PCA-reduced data for clustering analysis with Seurat v3.

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