SCALE method for single-cell ATAC-seq analysis via latent feature extraction
Single-cell ATAC-seq data is challenging to analyse for reasons such as high dimensionality and sparsity. Here, the authors develop SCALE, a deep learning method that leverages latent feature extraction for various tasks of scATACseq data analysis.
Enregistré dans:
Auteurs principaux: | Lei Xiong, Kui Xu, Kang Tian, Yanqiu Shao, Lei Tang, Ge Gao, Michael Zhang, Tao Jiang, Qiangfeng Cliff Zhang |
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Format: | article |
Langue: | EN |
Publié: |
Nature Portfolio
2019
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Sujets: | |
Accès en ligne: | https://doaj.org/article/9307133826f6483aacbf4da911ec0cc4 |
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