SINCERA: A Breakthrough Tool for Single-Cell RNA Profiling
Published November 24, 2015
PLoS Computational Biology
A new open-source analytic tool called SINCERA is helping scientists gain new insight into how organs form in a developing embryo.
A paper describing the tool appeared Nov. 24, 2015, in PLoS Computational Biology. A team led by Yan Xu, PhD, Pulmonary Biology and Biomedical Informatics, and Jeffrey Whitsett, MD, co-director, Perinatal Institute, developed the tool.
Single-cell transcriptomics is a powerful way to profile cell-to-cell variability on a genomic scale. Its use will advance decades of research, led in large part at Cincinnati Children’s, to produce the world’s most-detailed map of lung development.
“A thorough understanding of the cells and gene expression driving normal lung maturation will promote the understanding of lung diseases in both infants and children,” Xu says. “However, the paucity of analytic tools for processing extensive single-cell genomic data has been a major challenge.”
SINCERA is an acronym drawn from “a computational pipeline for single-cell RNA-seq profiling analysis.” The tool allows investigators to use standard desktop and laptop computers for data filtering, clustering, cell type identification, gene signature prediction and more.
The tool makes it easier to identify major cell types, the gene signatures specific to cell types, and the driving forces of given cell types. Among its early uses: producing multiple single-cell datasets reflecting different time points in organ development.
The NIH-funded Lung-MAP consortium has supported this project as part of its mission to develop a comprehensive atlas of lung development. SINCERA and LungGENS, a related tool, are both freely available to the research community.
