NSForest Documentation

Contents

• Installation
• Tutorial nsforesting
  • Setting up environment
  • Data Exploration
    • Loading h5ad AnnData file
    • Defining cluster_header as cell type annotation.
    • Defining output_folder for saving results
    • Looking at sample labels
    • Looking at genes
    • Checking cell annotation sizes
  • Preprocessing
    • Generating scanpy dendrogram
    • Calculating cluster medians per gene
    • Calculating binary scores per gene per cluster
    • Plotting median and binary score distributions
    • Saving preprocessed AnnData as new h5ad
  • Running NS-Forest
  • Plotting scanpy dot plot, violin plot, matrix plot for NS-Forest markers
    • Plotting classification metrics from NS-Forest results
    • Plotting individual classification metrics
    • Plotting metrics vs clusterSize
• Tutorial evaluating
  • Setting up environment
  • Data Exploration
    • Loading h5ad AnnData file
  • Evaluating input marker list
    • Getting marker list in dictionary format: {cluster: marker_list}
  • Plotting scanpy dot plot, violin plot, matrix plot for input marker list
    • Plotting classification metrics from NS-Forest results
    • Plotting individual classification metrics
    • Plotting metrics vs clusterSize
• Tutorial spatial
  • Setting up environment
  • Filtering genes to optimize spatial gene panels.
  • Calculating medians and binary scores per cluster
  • Running NS-Forest
• Preprocessing
  • dendrogram()
  • prep_medians()
  • get_medians()
  • prep_binary_scores()
  • plot_varm()
  • spaceTx_genefilter()
• NSForest
  • NSForest()
• Evaluating
  • DecisionTree()
  • add_fraction()
• Plotting with scanpy
  • dotplot()
  • stackedviolin()
  • matrixplot()
• Plotting with plotly
  • boxplot()
  • scatter_w_clusterSize()
• Utility Functions
  • str_to_list()
  • prepare_markers()