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BEDbase: a unified platform for genomic regions

Likelihood

BEDbase
BEDboss
Geniml
Gtars
Manuscripts

BEDbase: a unified platform for genomic regions

BEDbase
BEDbase
- User guides
  User guides
- Developer guides
  Developer guides
  - 📇 BEDhost API server
    
    📇 BEDhost API server
    
    Building docker image
    
    Deploy API
    
    Changelog
  - 🔌 BBConf configuration
    
    🔌 BBConf configuration
    
    Overview
    
    Guide
    
    Changelog
  - 🧰 BEDBoss processing pipeline
  - 🔄 BEDbase auto uploader
  - 📜 Configuration file
- Reference
  Reference
BEDboss
BEDboss
- Tutorials
  Tutorials
  - Python modules
    Python modules
    
    BEDboss run-pep
    
    BEDboss-all pipeline
    
    BEDmaker
    
    BEDstat
    
    BEDbuncher
    
    BEDindex
    
    BEDclassifier
    
    Ref_genome validator
  - Command line interface
  - BEDMS tutorial
- How to guides
  How to guides
- Reference
  Reference
  - How to cite
  - Changelog
Geniml
Geniml
- Getting Started
  Getting Started
  - Module overviews
- BBclient
  BBclient
  - Cache BED files with BBClient
  - Use BED cache in R
- Atacformer
  Atacformer
  - Getting started
    Getting started
    
    Core concepts
    
    Quickstart
  - Tutorials
    Tutorials
    
    Generating a UMAP from fragments files
    
    Example Brain3k Processing
    
    Visualizing new embeddings in the latent space of a reference
    
    Training
    Training
    
    Pre-tokenize data for training
    
    Train a model from scratch
    
    Fine-tune a model
  - Local compute guides
    Local compute guides
    
    Compute requirements
    
    Using atacformer locally
    
    Using atacformer with Apple Silicon
- How-to guides
  How-to guides
  - Train region2vec embeddings
  - Train BEDspace model
    Train BEDspace model
    
    Train BEDSpace embeddings
    
    BEDspace results notebook
  - Use scEmbed model
    Use scEmbed model
    
    Train single-cell embeddings
    
    Populate a vector store
    
    Predict cell-types using KNN
  - Evaluate embeddings
  - Create consensus peaks with CLI
  - Create consensus peaks with Python
  - Assess universe fit
  - Fine-tune embeddings
  - Randomize bed files
  - Create evaluation dataset with bedshift
  - Create search backend
- Reference
  Reference
  - How to cite
  - Python API documentation
    Python API documentation
    
    Assess
    
    Atacformer
    
    BBClient
    
    BEDshift
    
    BEDspace
    
    Craft
    
    Evaluation
    
    Geneformer
    
    I/O
    
    Likelihood Likelihood
    Table of contents
    
    likelihood
    
    Functions
    
    Models
    
    Region2Vec
    
    scEmbed
    
    Search
    
    Text2BedNN
    
    Tokenization
    
    Universe
    
    Utilities
  - Support
  - Contributing
  - Changelog
Gtars
Gtars
- 💿 Install
- Modules
  Modules
- Bindings
  Bindings
  - Python
    Python
    
    Python
    
    Digests
    
    RegionSet
    
    RefgetStore
    
    Tokenizers
  - Wasm
    Wasm
    
    Overview
    
    Overlappers
  - CLI
  - R
    R
    
    R
    
    RefgetStore
- Reference
  Reference
Manuscripts
Manuscripts
- How to cite
- Published manuscripts
  Published manuscripts

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