HVP

HVP estimates the proportion of variance associated with batch effects in a data set.

Key Features:

• Quantitative batch effect metric: HVP provides a numerical estimate of variance proportion attributable to batch effects.
• Hierarchical variance partitioning: The method partitions variance components in a hierarchical framework to quantify batch-related variation.

Scientific Applications:

• Batch effect quantification: HVP enables researchers to measure and assess the magnitude of batch effects in genomic and other high-dimensional data sets.

Methodology:

HVP uses hierarchical variance partitioning to estimate the proportion of variance associated with batch effects.