Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8918078 | Current Opinion in Systems Biology | 2018 | 7 Pages |
Abstract
The recent advent of highly parallelizable single-cell RNA-sequencing technologies has opened a new window into the study of cell differentiation, commitment, and diversity. Rapid advances in the development of these technologies are being accompanied by the design of computational methods tailored to address the challenges presented by the analysis of single-cell RNA-sequencing data. This review provides a concise overview of some of the steps, algorithms, and approaches that are currently used in the analysis of single-cell RNA-sequencing data, with an emphasis on recent developments.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Pablo G. Camara,