Autoencoder-based cluster ensembles for single-cell RNA-seq data analysis

Autoencoder-based cluster ensembles for single-cell RNA-seq data analysis

Abstract Background Single-cell RNA-sequencing (scRNA-seq) is a transformative technology, allowing global transcriptomes of individual cells to be profiled with high accuracy. An essential task in scRNA-seq data analysis is the identification of cell types from complex samples or tissues profiled i...

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Bibliographic Details
Main Authors: Thomas A. Geddes, Taiyun Kim, Lihao Nan, James G. Burchfield, Jean Y. H. Yang, Dacheng Tao, Pengyi Yang
Format: Article
Language:English
Published: BMC 2019-12-01
Series:BMC Bioinformatics
Subjects:
Autoencoder
Cluster ensemble
Single cells
scRNA-seq
Single-cell transcriptome
Cell type identification
Online Access:https://doi.org/10.1186/s12859-019-3179-5

Internet

https://doi.org/10.1186/s12859-019-3179-5

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