News from the CRG and DCEXS-UPF
A group of scientists of the CNAG-CRG, in collaboration with researchers from the University Pompeu Fabra (UPF) and the Spanish Biomedical Research Consortium on Rare Diseases (CIBERER), has now developed an efficient computational framework that enables processing, analysis and interpretation of big-scale single-cell experiments. The group illustrated the power of their strategy by analyzing one of the largest single-cell studies with 1.3 million individual cells of the developing mouse brain.
“BigSCale is extremely powerful in identifying cell type-specific genes, which greatly helps in the downstream interpretation of experiments” says Holger Heyn, CNAG-CRG team leader and senior author of the study. The novelty of the analytic tool named “BigSCale” lies in a numerical model that sensitively determines differences between single cells. Having charted how individual cells differ from each other, they can be grouped together into populations of cells to describe the cellular complexity of a given tissue. As virtually all tissues are composed of different cell types and subtypes, such an analysis can guide an unbiased in-depth characterization without initial hypotheses. Differentially expressed marker genes between subpopulations help the researcher to link cells to prior knowledge about the tissue anatomy or to describe the functions of newly discovered cell types.
Iacono et al. bigSCale: an analytical framework for big-scale single-cell data. Genome Research. 2018. DOI: 10.1101/gr.230771.117