Tweedieverse
Tweedieverse is an R package for differential analysis of omics data implementing a range of statistical methodology based on the Tweedie distribution.
Unlike traditional single-omics tools, Tweedieverse is technology-agnostic and can be applied to both count and continuous measurements arising from diverse high-throughput technologies (e.g., transcript abundances from bulk and single-cell RNA-Seq studies in the form of UMI counts or non-UMI counts, microbiome taxonomic and functional profiles in the form of counts or relative abundances, and compound abundance levels or peak intensities from metabolomics and other mass spectrometry-based experiments, among others).
The software includes multiple analysis methods (e.g., self-adaptive, zero-inflated, and non-zero-inflated statistical models) as well as multiple customization options such as the inclusion of random effects and multiple covariates along with several data exploration capabilities and visualization modules in a unified estimation umbrella.
MaAsLin2
MaAsLin2 is comprehensive R package for efficiently determining multivariable association between phenotypes, environments, exposures, covariates and microbial meta-omics features. MaAsLin2 relies on general linear models to accommodate most modern epidemiological study designs, including cross-sectional and longitudinal, and offers a variety of data exploration, normalization, and transformation methods
MelonnPan
MelonnPan is a computational method for predicting metabolite compositions from microbiome sequencing data. It uses elastic net regularization to infer which sequencing features are predictive and combines these features to estimate the composite metabolome.
TweedSpot