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.

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Auteurs principaux: Lei Xiong, Kui Xu, Kang Tian, Yanqiu Shao, Lei Tang, Ge Gao, Michael Zhang, Tao Jiang, Qiangfeng Cliff Zhang
Format: article
Langue:EN
Publié: Nature Portfolio 2019
Sujets:
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Accès en ligne:https://doaj.org/article/9307133826f6483aacbf4da911ec0cc4
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