MultiBaC

MultiBaC corrects batch effects in multi-omic datasets to disentangle technical variability from biological signal.

Key Features:

• Implementation: Implemented as an R package.
• Multi-omic batch correction: Performs batch effect correction across multi-omic datasets combining diverse omics types.
• Explicit and hidden batch effects: Detects and corrects both explicit (known) and hidden (latent) batch effects.
• Disentangling omics and batch variables: Implements algorithms to disentangle the intertwined influences of omics type and batch variables.
• Graphical validation outputs: Provides graphical outputs for model validation and assessment of correction effectiveness.
• Empirical validation: Validated using Gene Expression Omnibus datasets GSE11521, GSE1002, GSE56622, and GSE43747.

Scientific Applications:

• Differential expression studies: Enables differential expression analyses by reducing technical artifacts that confound expression signals.
• Integrative multi-omics analyses: Supports integrative analyses by harmonizing data across omics platforms.
• Cross-platform data integration: Improves interpretation of biological variation in studies combining multiple omic technologies.

Methodology:

Implemented as an R package that applies algorithms to detect and correct explicit and hidden batch effects and to disentangle the influences of omics type and batch variables.