Original paper

Single-Cell Multi-omic Integration Compares and Contrasts Features of Brain Cell Identity

Cell45.50
Volume: 177, Issue: 7, Pages: 1873 - 1887.e17
Published: Jun 1, 2019
Abstract
Defining cell types requires integrating diverse single-cell measurements from multiple experiments and biological contexts. To flexibly model single-cell datasets, we developed LIGER, an algorithm that delineates shared and dataset-specific features of cell identity. We applied it to four diverse and challenging analyses of human and mouse brain cells. First, we defined region-specific and sexually dimorphic gene expression in the mouse bed...
Paper Details
Title
Single-Cell Multi-omic Integration Compares and Contrasts Features of Brain Cell Identity
Published Date
Jun 1, 2019
Journal
Volume
177
Issue
7
Pages
1873 - 1887.e17
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