DAssemble - Ensemble Models for Differential Analysis
The DAssemble package implements an ensemble framework for differential-abundance and differential-expression analysis across bulk RNA-seq, single-cell RNA-seq, and microbiome studies. It wraps a collection of popular DA/DE methods as core methods and combines them via Cauchy Combination Tests (CCT), optionally augmented by simple enhancers such as Wilcoxon, Kolmogorov–Smirnov, and presence–absence logistic regression.
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softwarestatisticalmethoddifferentialexpressionrnaseqsinglecellmicrobiomenormalizationregression
5.48 score 6 stars 3 scripts 593 downloadsHuMMANet - Curated Paired Human Microbiome-Metabolome Study Data
Provides access to curated paired human microbiome-metabolome study bundles available through Bioconductor ExperimentHub. The package organizes matched sample metadata, species abundance profiles, original and harmonized metabolite profiles, and study-specific annotation resources including metabolite identifier mappings, microbial producer annotations, disease associations, pathway annotations, and drug similarity matches. The resource is designed to support consistent and reproducible cross-study microbiome-metabolome analyses.
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experimentdataexperimenthubhomo_sapiens_datamicrobiomedatadatapkg
5.26 scoreIntegratedLearner - Integrated Multi-Omics Learning for Survival and Other Outcomes
Provides a unified interface for multi-omics prediction using early and late fusion for continuous, binary, multiclass, and survival outcomes. It supports both MultiAssayExperiment and PCL-style inputs, performs input validation and feature/sample harmonization across layers, and provides model fitting, prediction, plotting, and variable-importance utilities.
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softwareclassificationsurvivalmicrobiomeopenjdk
4.38 score 15 scriptsTweedieverse - Differential Analysis of Omics Data Based on the Tweedie Distribution
A toolkit for differential analysis of omics data. Implements a CPLM-based statistical workflow built 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 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.
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differentialexpressionsoftwarevisualizationcellbasedassaysatacseqmicrobiomemassspectrometrysinglecellmetabolomicsmetagenomicsworkflowstepmultiplecomparisonnormalizationregressionrnaseq
3.60 scoreTweedSpot - Self-Adaptive Spatial Tweedie Models for Spatially Variable Gene Detection
TweedSpot detects spatially variable genes (SVGs) in spatially resolved transcriptomics data using self-adaptive Tweedie generalized additive models with nonparametric spatial smoothing. The method models raw counts directly, avoiding the bias introduced by log-transformation, adapts a gene-specific Tweedie index parameter to the mean-variance relationship of each gene, and offers an optional two-part formulation to accommodate excess zeros. Inputs and outputs use the SpatialExperiment infrastructure for interoperability with the Bioconductor ecosystem.
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softwaretranscriptomicsgeneexpressionriboseqspatialregressionstatisticalmethoddifferentialexpressionqualitycontrol
3.30 score