A scalable unsupervised learning of scRNAseq data detects rare cells through integration of structure-preserving embedding, clustering and outlier detection.
Koushik MallickSikim ChakrabortySaurav MallikSanghamitra BandyopadhyayPublished in: Briefings Bioinform. (2023)
Keyphrases
- outlier detection
- unsupervised learning
- detect outliers
- structure preserving
- knowledge discovery
- high dimensional datasets
- parameter free
- detecting outliers
- categorical data
- data sets
- spectral clustering
- data mining techniques
- data points
- database
- multi dimensional data
- fraud detection
- detection algorithm
- high dimensional data
- computer vision
- dimensionality reduction
- clustering method
- spatial data
- pairwise
- data clustering
- pattern recognition
- training data
- sequential data
- clustering algorithm
- feature selection
- density based clustering
- data sources
- data mining