scAuto as a comprehensive framework for single-cell chromatin accessibility data analysis (2024)


Authors: Meiqin Gong, Yun Yu, Zixuan Wang, Junming Zhang, + 4, Xiongyi Wang, Cheng Fu, Yongqing Zhang, and Xiaodong Wang (Less)

Published: 09 July 2024 Publication History

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    Interpreting single-cell chromatin accessibility data is crucial for understanding intercellular heterogeneity regulation. Despite the progress in computational methods for analyzing this data, there is still a lack of a comprehensive analytical framework and a user-friendly online analysis tool. To fill this gap, we developed a pre-trained deep learning-based framework, single-cell auto-correlation transformers (scAuto), to overcome the challenge. Following DNABERT’s methodology of pre-training and fine-tuning, scAuto learns a general understanding of DNA sequence’s grammar by being pre-trained on unlabeled human genome via self-supervision; it is then transferred to the single-cell chromatin accessibility analysis task of scATAC-seq data for supervised fine-tuning. We extensively validated scAuto on the Buenrostro2018 dataset, demonstrating its superior performance on chromatin accessibility prediction, single-cell clustering, and data denoising. Based on scAuto, we further developed an interactive web server for single-cell chromatin accessibility data analysis. It integrates tutorial-style interfaces for those with limited programming skills. The platform is accessible at To our knowledge, this work is expected to help analyze single-cell chromatin accessibility data and facilitate the development of precision medicine.


    Present a framework for single-cell chromatin accessibility analysis.

    Develop an online analysis platform, scAuto.

    Conduct extensive experiments and achieve the state-of-the-art performance.



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    • RoboCOP: Multivariate State Space Model Integrating Epigenomic Accessibility Data to Elucidate Genome-Wide Chromatin Occupancy

      Research in Computational Molecular Biology


      Chromatin is the tightly packaged structure of DNA and protein within the nucleus of a cell. The arrangement of different protein complexes along the DNA modulates and is modulated by gene expression. Measuring the binding locations and level of ...

      Read More

    • Genome‐wide prediction of chromatin accessibility based on gene expression


      Decoding gene regulation in a biological system requires information from both transcriptome and regulome. While multiple high‐throughput transcriptome and regulome mapping technologies are available, transcriptome profiling is more widely used. ...

        Open chromatin marks active regulatory elements in the genome and is important for understanding gene regulation. This article reviews methods for predicting chromatin accessibility using widely available gene expression data and discusses their ...

        Read More

      • Attentive gated neural networks for identifying chromatin accessibility


        Accessible chromatin is associated strongly with active gene regulatory regions. Enhancers and promoters commonly occur in accessible chromatin, and systematically discovering functional sites is indispensable at the whole genome level. However, ...

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      Information & Contributors


      Published In

      scAuto as a comprehensive framework for single-cell chromatin accessibility data analysis (1)

      Computers in Biology and Medicine Volume 171, Issue C

      Mar 2024

      1547 pages


      Issue’s Table of Contents

      Elsevier Ltd.


      Pergamon Press, Inc.

      United States

      Publication History

      Published: 09 July 2024

      Author Tags

      1. Single-cell genomics
      2. Chromatin accessibility
      3. Data analysis tools
      4. Web server
      5. Deep learning


      • Research-article


      scAuto as a comprehensive framework for single-cell chromatin accessibility data analysis (2)

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