Sensitive detection of rare disease-associated cell subsets via representation learning.
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ABSTRACT:
SUBMITTER: Arvaniti E
PROVIDER: S-EPMC5384229 | biostudies-literature | 2017 Apr
REPOSITORIES: biostudies-literature
Publications
Sensitive detection of rare disease-associated cell subsets via representation learning.
Arvaniti Eirini E Claassen Manfred M
Nature communications 20170406
Rare cell populations play a pivotal role in the initiation and progression of diseases such as cancer. However, the identification of such subpopulations remains a difficult task. This work describes CellCnn, a representation learning approach to detect rare cell subsets associated with disease using high-dimensional single-cell measurements. Using CellCnn, we identify paracrine signalling-, AIDS onset- and rare CMV infection-associated cell subsets in peripheral blood, and extremely rare leuka ...[more]
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