CytoSEE Tutorial

  • CytoSEE: a web-based toolkit for automatic computation and evaluation of cytometry data.
  • CytoSEE:, a web-based cytometry tool for preprocessing, clustering, visualization and auto-labeling.
    - Clustering methods: To deal with large-scale dataset, we developed a method called Consboost, which combines consensus clustering and AdaBoost. In addition, we also integrated other 4 algorithms with high performance to fit different situations.
    - Cell labeling: we wrote the module called PhenoCL, which can predict the cell ontology based on the marker expression.
    - Visualization: We introduced multiple methods like t-SNE, largeVis, MST and heatmap to illustrate the results in many aspects.
    - Periodic update: CytoSEE will update regularly.

  • 1 Single File Analysis

  • 1.1 File Upload
    single file analysis entrance
  • 1.2 Data Preview
    Data preview
  • 1.3 Quality control
    choose qc method
  • 1.3.1 Quality control manually
    Quality control manually
  • 1.4 Cell clustering
    cell clustering
  • 1.5 Cluster Label Generation
    Label the clustering
  • 1.6 Divisive marker tree Generation
    Divisive marker tree
  • 1.7 Clusters label information
    Clusters label information
  • 1.8.1 Visualization -- Scatter Plot
    scatter plot
  • 1.8.2 Visualization -- Minumum Spanning Tree Plot
    Minumum Spanning Tree Plot
  • 1.8.3 Visualization -- Heatmap
    Heatmap
  • 1.8.4 Visualization -- Population Marker
    Population Marker
  • 1.8.5 Visualization -- Project information report
    Project information report
  • 1.8.6 Visualization -- Cluster information report
    Cluster information report

  • 2 Rdata Display

  • 2.1 File Upload

    Rdata display entrance

  • Remaining steps refer to the Step 1.5

©2019. Ming Chen's Group of Bioinformatics. All rights reserved