scglue

Contents:

  • Installation guide
  • Tutorials
    • Stage 1: Data preprocessing
    • Stage 2: Model training
    • Stage 3: Regulatory inference
    • Extra: Model training on partially paired data
  • Example datasets
  • API documentation
  • Release notes
  • Developer guide
  • Credits
scglue
  • Tutorials
  • View page source

Tutorials

An scglue workflow can be divided into the following two stages. We provide separate tutorials for each stage, using the integration of scRNA-seq and scATAC-seq data as an example.

  • Stage 1: Data preprocessing
    • Read data
    • Preprocess scRNA-seq data
    • Preprocess scATAC-seq data
    • Construct prior regulatory graph
      • Obtain genomic coordinates
      • Graph construction
    • Save preprocessed data files
  • Stage 2: Model training
    • Read preprocessed data
    • Configure data
    • Train GLUE model
    • Check integration diagnostics
    • Apply model for cell and feature embedding
  • Stage 3: Regulatory inference
    • Read intermediate results
    • Cis-regulatory inference with GLUE feature embeddings
    • Visualize the inferred cis-regulatory regions
    • Construct TF-gene regulatory network from inferred cis-regulatory regions
      • Draft a coexpression-based network
      • Generate TF cis-regulatory ranking bridged by ATAC peaks
      • Generate TF cis-regulatory ranking with proximal promoters (optional)
      • Prune coexpression network using cis-regulatory ranking
    • Visualize the inferred TF-target gene network
  • Extra: Model training on partially paired data
    • Read preprocessed data
    • Label paired cells via obs_names
    • Configure data
    • Train GLUE model
    • Continue as in stage 2
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