PCA via joint graph Laplacian and sparse constraint: Identification of differentially expressed genes and sample clustering on gene expression data.
Chun-Mei FengYong XuMi-Xiao HouLing-Yun DaiJunliang ShangPublished in: BMC Bioinform. (2019)
Keyphrases
- gene expression data
- differentially expressed genes
- microarray
- microarray data
- microarray data analysis
- gene expression
- graph laplacian
- spectral clustering
- high dimensional
- gene expression analysis
- gene expression profiles
- high dimensionality
- k means
- principal component analysis
- gene selection
- high dimensional data
- cluster analysis
- clustering algorithm
- high throughput
- clustering method
- dimensionality reduction
- random walk
- data points
- low dimensional
- weighted graph
- data clustering
- microarray datasets
- gene regulatory networks
- feature selection
- sample size
- data sets
- negative matrix factorization
- gene ontology
- unsupervised learning
- probabilistic model
- biological data
- sparse coding
- pairwise
- linear discriminant analysis