Scalable analysis of cell-type composition from single-cell transcriptomics using deep recurrent learning

被引：0
|
作者：
Yue Deng
Feng Bao
Qionghai Dai
Lani F. Wu
Steven J. Altschuler
机构：
[1] University of California,Department of Pharmaceutical Chemistry
[2] San Francisco,Department of Automation, Tsinghua National Laboratory for Information Science and Technology
[3] Tsinghua University,undefined
来源：
Nature Methods | 2019年 / 16卷
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摘要：
Recent advances in large-scale single-cell RNA-seq enable fine-grained characterization of phenotypically distinct cellular states in heterogeneous tissues. We present scScope, a scalable deep-learning-based approach that can accurately and rapidly identify cell-type composition from millions of noisy single-cell gene-expression profiles.
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页码：311 / 314
页数：3
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