Sensitive detection of rare disease-associated cell subsets via representation learning
While rare cell subpopulations frequently make the difference between health and disease, their detection remains a challenge. Here, the authors devise CellCnn, a representation learning approach to detecting such rare cell populations from high-dimensional single cell data, and, among other example...
Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
Nature Publishing Group
2017-04-01
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Series: | Nature Communications |
Online Access: | https://doi.org/10.1038/ncomms14825 |