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@aertslab

aertslab

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  1. SCope SCope Public

    Fast visualization tool for large-scale and high dimensional single-cell data

    Python 74 15

  2. pySCENIC pySCENIC Public

    pySCENIC is a lightning-fast python implementation of the SCENIC pipeline (Single-Cell rEgulatory Network Inference and Clustering) which enables biologists to infer transcription factors, gene reg…

    Python 534 195

  3. AUCell AUCell Public

    AUCell: score single cells with gene regulatory networks

    R 166 29

  4. pycisTopic pycisTopic Public

    pycisTopic is a Python module to simultaneously identify cell states and cis-regulatory topics from single cell epigenomics data.

    Jupyter Notebook 74 12

  5. scenicplus scenicplus Public

    SCENIC+ is a python package to build gene regulatory networks (GRNs) using combined or separate single-cell gene expression (scRNA-seq) and single-cell chromatin accessibility (scATAC-seq) data.

    Jupyter Notebook 233 45

  6. CREsted CREsted Public

    CREsted is a Python package for training sequence-based deep learning models on scATAC-seq data, for capturing enhancer code and for designing cell type-specific sequences.

    Python 44 8

Repositories

Showing 10 of 78 repositories
  • TF-MInDi Public

    Transcription Factor Motifs and Instances Discovery

    aertslab/TF-MInDi’s past year of commit activity
    Python 6 MIT 0 0 0 Updated Sep 4, 2025
  • HyDrop_v2_paper Public

    To facilitate the cost-effective generation of large scATAC-seq atlases for deep learning model training, we developed a new version of the open-source microfluidic system HyDrop with increased sensitivity and scale: HyDrop v2.

    aertslab/HyDrop_v2_paper’s past year of commit activity
    Jupyter Notebook 0 MIT 0 0 0 Updated Sep 1, 2025
  • CREsted-paper Public
    aertslab/CREsted-paper’s past year of commit activity
    Jupyter Notebook 2 MIT 0 0 0 Updated Aug 29, 2025
  • CREsted Public

    CREsted is a Python package for training sequence-based deep learning models on scATAC-seq data, for capturing enhancer code and for designing cell type-specific sequences.

    aertslab/CREsted’s past year of commit activity
    Python 44 8 6 5 Updated Aug 21, 2025
  • pycisTopic Public

    pycisTopic is a Python module to simultaneously identify cell states and cis-regulatory topics from single cell epigenomics data.

    aertslab/pycisTopic’s past year of commit activity
    Jupyter Notebook 74 12 52 4 Updated Jul 28, 2025
  • single_cell_toolkit Public

    Tools for correcting single cell barcodes for various scATAC-seq techniques and creating fragment files and spltting BAM files per cluster.

    aertslab/single_cell_toolkit’s past year of commit activity
    Shell 28 4 3 0 Updated Jun 30, 2025
  • pySCENIC Public

    pySCENIC is a lightning-fast python implementation of the SCENIC pipeline (Single-Cell rEgulatory Network Inference and Clustering) which enables biologists to infer transcription factors, gene regulatory networks and cell types from single-cell RNA-seq data.

    aertslab/pySCENIC’s past year of commit activity
    Python 534 GPL-3.0 195 227 3 Updated Jun 26, 2025
  • scenicplus_core Public

    Collection of common algorithms and functions for all SCENIC+ related tools.

    aertslab/scenicplus_core’s past year of commit activity
    Rust 0 0 0 0 Updated Jun 20, 2025
  • create_cisTarget_databases Public

    Create cisTarget databases

    aertslab/create_cisTarget_databases’s past year of commit activity
    Python 53 7 36 0 Updated Jun 18, 2025
  • mango-ingest Public Forked from kuleuven/mango-ingest
    aertslab/mango-ingest’s past year of commit activity
    Python 0 BSD-3-Clause 2 0 0 Updated Jun 12, 2025
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