Abstract
For decades, people have been trying to define cell type with the combination of expressed genes. The choice of the limited number of genes for the classification limits the precision of this system. Here, we build a “single-cell Mouse Cell Atlas (scMCA) analysis” pipeline based on scRNA-seq datasets covering all mouse cell types. We build the scMCA reference and then use the tool “scMCA” to match single-cell digital expression to its closest cell type.
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Sun, H., Zhou, Y., Fei, L., Chen, H., Guo, G. (2019). scMCA: A Tool to Define Mouse Cell Types Based on Single-Cell Digital Expression. 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_6
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DOI: https://doi.org/10.1007/978-1-4939-9057-3_6
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Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-9056-6
Online ISBN: 978-1-4939-9057-3
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