Linear Models for Sequence Count Data
Simulation function soley for testing and exploring ALDEx3, Truth is i...
Simulation for testing mixed effects models.
Calculate p-values adjusting for changes in sign as described by Nixon...
ALDEx3 Linear Models
Default CLR-based scale model (with optional scale uncertainty)
Coefficient-based scale model with user-specified prior on fixed effec...
Cohen's D
Combine output from aldex streams (internal only)
Freaking Fask Linear Models
Closure operation
Test object contains elements
Function for sampling Dirichlet random variables (base-2 normalized vi...
Sample-specific scale model with user-specified mean and variance/cova...
Implementation of SR-MEM: scale-reliant mixed effects models.
Summary Method for ALDEx3 Objects
TSS-centered scale model (with optional scale uncertainty)
Provides scalable generalized linear and mixed effects models tailored for sequence count data analysis (e.g., analysis of 16S or RNA-seq data). Uses Dirichlet-multinomial sampling to quantify uncertainty in relative abundance or relative expression conditioned on observed count data. Implements scale models as a generalization of normalizations which account for uncertainty in scale (e.g., total abundances) as described in Nixon et al. (2025) <doi:10.1186/s13059-025-03609-3> and McGovern et al. (2025) <doi:10.1101/2025.08.05.668734>.