Abstract
Single-cell RNA-Sequencing is a pioneering extension of bulk-based RNA-Sequencing technology. The “guilt-by-association” heuristic has led to the use of gene co-expression networks to identify genes that are believed to be associated with a common cellular function. Many methods that were developed for bulk-based RNA-Sequencing data can continue to be applied to single-cell data, and several of the most widely used methods are explored. Several methods for leveraging the novel time information contained in single-cell data when constructing gene co-expression networks, which allows for the incorporation of directed associations, are also discussed.
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Lamere, A.T., Li, J. (2019). Inference of Gene Co-expression Networks from Single-Cell RNA-Sequencing Data. In: Yuan, GC. (eds) Computational Methods for Single-Cell Data Analysis. Methods in Molecular Biology, vol 1935. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-9057-3_10
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DOI: https://doi.org/10.1007/978-1-4939-9057-3_10
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