Search Results for author:
Found 4 papers, 3 papers with code
Outcome-guided Sparse K-means for Disease Subtype Discovery via Integrating Phenotypic Data with High-dimensional Transcriptomic Data
We demonstrated the superior performance of the GuidedSparseKmeans by comparing with existing clustering methods in simulations and applications of high-dimensional transcriptomic data of breast cancer and Alzheimer's disease.
A sparse negative binomial mixture model for clustering RNA-seq count data
With the prevalence of RNA-seq technology and lack of count data modeling for clustering, the current practice is to normalize count expression data into continuous measures and apply existing models with Gaussian assumption.
P-value evaluation, variability index and biomarker categorization for adaptively weighted Fisher's meta-analysis method in omics applications
Meta-analysis methods have been widely used to combine results from multiple clinical or genomic studies to increase statistical power and ensure robust and accurate conclusion.
Methodology Applications
Bayesian latent hierarchical model for transcriptomic meta-analysis to detect biomarkers with clustered meta-patterns of differential expression signals
Due to rapid development of high-throughput experimental techniques and fast dropping prices, many transcriptomic datasets have been generated and accumulated in the public domain.
Applications
