Unsupervised Single-Cell Clustering with Asymmetric Within-Sample Transformation and Per-Cluster Supervised Features Selection
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Publisher
Springer US
Link
https://link.springer.com/content/pdf/10.1007/978-1-0716-3886-6_8
Reference16 articles.
1. Risso D, Pagnotta SM (2021) Per-sample standardization and asymmetric winsorization lead to accurate clustering of RNA-seq expression profiles. Bioinformatics 37(16):2356–2364. https://doi.org/10.1093/bioinformatics/btab091
2. Calinski T, Harabasz J (1974) A dendrite method for cluster analysis. Commun Stat 3(1):1–27. https://doi.org/10.1080/03610927408827101
3. Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15(12):550. https://doi.org/10.1186/s13059-014-0550-8
4. Pagnotta SM (2023) Unsupervised clustering of single-cells with asymmetric within-sample transformation, and per cluster supervised features selection. (supporting code). https://github.com/stefanoMP/MiMB
5. Kessenbrock K (2018) Sample GSM3099847 of adult human breast epithelium. https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM3099847
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