projectR

projectR projects data into spaces defined by PCA, CoGAPS, NMF, correlation, and clustering to enable cross-dataset pattern transfer and biological interpretation.

Key Features:

• PCA Projection: Projects data into principal component spaces defined by PCA.
• CoGAPS Projection: Projects data into pattern spaces defined by CoGAPS.
• NMF Projection: Projects data into basis spaces defined by non-negative matrix factorization.
• Correlation Projection: Projects data into correlation-defined spaces.
• Clustering Projection: Projects data into spaces defined by clustering results.

Scientific Applications:

• Cross-dataset Pattern Transfer: Enables projection of weights and patterns learned from one dataset onto new data for comparative analysis.
• Dimensionality Reduction Integration: Facilitates biological interpretation by mapping new data into previously defined reduced-dimensional spaces.

Methodology:

projectR implements projection of data into spaces defined by PCA, CoGAPS, NMF, correlation, and clustering.