Adapted single-cell consensus clustering (adaSC3)

Fuetterer C, Augustin T, Fuchs C (2020)
Advances in Data Analysis and Classification volume 14(4): 885–896.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
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Autor*in
Fuetterer, Cornelia; Augustin, Thomas; Fuchs, ChristianeUniBi
Abstract / Bemerkung
The analysis of single-cell RNA sequencing data is of great importance in health research. It challenges data scientists, but has enormous potential in the context of personalized medicine. The clustering of single cells aims to detect different subgroups of cell populations within a patient in a data-driven manner. Some comparison studies denote single-cell consensus clustering (SC3), proposed by Kiselev et al. (Nat Methods 14(5):483-486, 2017), as the best method for classifying single-cell RNA sequencing data. SC3 includes Laplacian eigenmaps and a principal component analysis (PCA). Our proposal of unsupervised adapted single-cell consensus clustering (adaSC3) suggests to replace the linear PCA by diffusion maps, a non-linear method that takes the transition of single cells into account. We investigate the performance of adaSC3 in terms of accuracy on the data sets of the original source of SC3 as well as in a simulation study. A comparison of adaSC3 with SC3 as well as with related algorithms based on further alternative dimension reduction techniques shows a quite convincing behavior of adaSC3.
Stichworte
Diffusion maps; Non-linear embedding; Single-cell consensus clustering; Simulation data; Single-cell RNA sequencing data
Erscheinungsjahr
2020
Zeitschriftentitel
Advances in Data Analysis and Classification volume
Band
14
Ausgabe
4
Seite(n)
885–896
ISSN
1862-5347
eISSN
1862-5355
Page URI
https://pub.uni-bielefeld.de/record/2950212

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Fuetterer C, Augustin T, Fuchs C. Adapted single-cell consensus clustering (adaSC3). Advances in Data Analysis and Classification volume. 2020;14(4):885–896.
Fuetterer, C., Augustin, T., & Fuchs, C. (2020). Adapted single-cell consensus clustering (adaSC3). Advances in Data Analysis and Classification volume, 14(4), 885–896. doi:10.1007/s11634-020-00428-1
Fuetterer, C., Augustin, T., and Fuchs, C. (2020). Adapted single-cell consensus clustering (adaSC3). Advances in Data Analysis and Classification volume 14, 885–896.
Fuetterer, C., Augustin, T., & Fuchs, C., 2020. Adapted single-cell consensus clustering (adaSC3). Advances in Data Analysis and Classification volume, 14(4), p 885–896.
C. Fuetterer, T. Augustin, and C. Fuchs, “Adapted single-cell consensus clustering (adaSC3)”, Advances in Data Analysis and Classification volume, vol. 14, 2020, pp. 885–896.
Fuetterer, C., Augustin, T., Fuchs, C.: Adapted single-cell consensus clustering (adaSC3). Advances in Data Analysis and Classification volume. 14, 885–896 (2020).
Fuetterer, Cornelia, Augustin, Thomas, and Fuchs, Christiane. “Adapted single-cell consensus clustering (adaSC3)”. Advances in Data Analysis and Classification volume 14.4 (2020): 885–896.

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