IFAA

IFAA offers a robust approach to make inference on the association of covariates with the absolute abundance (AA) of microbiome in an ecosystem.

Key Features:

• Absolute abundance inference from relative abundance data: The method can be directly applied to relative abundance (RA) data to make inference on AA because the ratio of two RA is equal to the ratio of their AA.
• Confounder adjustment: The algorithm estimates and tests associations of interest while adjusting for potential confounders, with estimates that have interpretation like typical regression analysis.
• High-dimensional covariate handling: High-dimensional covariates are handled with regularization and implemented by parallel computing.
• Automatic false discovery rate control: False discovery rate is automatically controlled by this approach.
• Zero handling: Zeros do not need to be imputed by a positive value for the analysis.
• Abundance ratio analysis: The package includes the MZILN function for estimating and testing associations of abundance ratios with covariates.

Scientific Applications:

• Microbiome absolute abundance association studies: Inference on the association of covariates with the absolute abundance of microbiome in an ecosystem.
• Relative abundance-based microbiome analysis: Analysis of relative abundance data to infer associations with absolute abundance without requiring imputation of zero values.
• Abundance ratio association testing: Estimation and testing of associations between abundance ratios and covariates using the MZILN function.

Methodology:

The method uses regularization for high-dimensional covariates and is implemented by parallel computing.