Article

Principal component analysis-based unsupervised feature extraction applied to single-cell gene expression analysis <sup>1</sup>

2018-05-02

Abstract excerpt

Due to missed sample labeling, unsupervised feature selection during single-cell (sc) RNA-seq can identify critical genes under the experimental conditions considered. In this paper, we applied principal component analysis (PCA)-based unsupervised feature extraction (FE) to identify biologically relevant genes from mouse and human embryonic brain development expression profiles retrieved by scRNA-seq. When evaluat...

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Literature Corpus work: f14596fa-db32-5e85-806c-3b8a661cfc0c
DOI: 10.1101/312892

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