Detecting somatic mutations in single-cell data sets
Author:
Publisher
Springer Science and Business Media LLC
Subject
Biomedical Engineering,Molecular Medicine,Applied Microbiology and Biotechnology,Bioengineering,Biotechnology
Link
https://www.nature.com/articles/s41587-023-01883-9.pdf
Reference5 articles.
1. Svensson, V., Vento-Tormo, R. & Teichmann, S. A. Exponential scaling of single-cell RNA-seq in the past decade. Nat. Protoc. 13, 599–604 (2018). This article provides an overview of the technological advancements underpinning the unparalleled increase in scale and resolution of single-cell RNA-seq methods.
2. Nam, A. S., Chaligne, R. & Landau, D. A. Integrating genetic and non-genetic determinants of cancer evolution by single-cell multi-omics. Nat. Rev. Genet. 22, 3–18 (2021). A comprehensive review of single-cell methods developed for studying the impact of genetic and epigenetic aberrations on cell function in the context of cancer.
3. Kakiuchi, N. & Ogawa, S. Clonal expansion in non-cancer tissues. Nat. Rev. Cancer 21, 239–256 (2021). A comprehensive review of somatic evolution in histologically normal tissues.
4. Van Egeren, D. et al. Reconstructing the lineage histories and differentiation trajectories of individual cancer cells in myeloproliferative neoplasms. Cell Stem Cell 28, 514–523.e9 (2021). This paper illustrates the potential of mapping genotypes to phenotypes at single-cell resolution to study the impact of somatic mutations on cell differentiation trajectories.
5. Muyas, F., Zapata, L., Guigó, R. & Ossowski, S. The rate and spectrum of mosaic mutations during embryogenesis revealed by RNA sequencing of 49 tissues. Genome Med. 12, 49 (2020). This paper reports the patterns and rates of mutations detected using bulk RNA-seq data from diverse non-neoplastic tissue samples.
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