Ensemble learning for classifying single-cell data and projection across reference atlases

SUMMARY: Single-cell data are being generated at an accelerating pace. How best to project data across single-cell atlases is an open problem. We developed a boosted learner that overcomes the greatest challenge with status quo classifiers: low sensitivity, especially when dealing with rare cell typ...

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Bibliographic Details
Published in:Bioinformatics
Main Authors: Wang, Lin, Catalan, Francisca, Shamardani, Karin, Babikir, Husam, Diaz, Aaron
Format: Artigo
Language:Inglês
Published: Oxford University Press 2020
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Applications Notes
Online Access:https://ncbi.nlm.nih.gov/pmc/articles/PMC7267838/
https://ncbi.nlm.nih.gov/pubmed/32105316
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bioinformatics/btaa137
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