3D computational reconstruction of tissues with hollow spherical morphologies using single-cell gene expression data.

ABSTRACT: Single-cell gene expression analysis has contributed to a better understanding of the transcriptional heterogeneity in a variety of model systems, including those used in research in developmental, cancer and stem cell biology. Nowadays, technological advances facilitate the generation of large gene expression data sets in high-throughput format. Strategies are needed to pertinently visualize this information in a tissue structure-related context, so as to improve data analysis and aid the drawing of meaningful conclusions. Here we describe an approach that uses spatial properties of the tissue source to enable the reconstruction of hollow sphere-shaped tissues and organs from single-cell gene expression data in 3D space. To demonstrate our method, we used cells of the mouse otocyst and th

SUBMITTER: Durruthy-Durruthy R 

PROVIDER: S-EPMC4523134 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature