Kim‐Anh Lê Cao

MINT Block integrates multi-omics data across studies to identify generalisable signatures while accounting for study-specific variation, improving prediction accuracy.

DIVAS identifies shared and individual variations in multiomics data, revealing partially shared patterns missed by existing methods.

The paper examines how marine reserves affect seawater microbial communities in the Great Barrier Reef, finding distinct microbiomes between protected and fished areas.

The paper presents a microbial genomes database for the Great Barrier Reef, highlighting underrepresented prokaryotic and viral genomes and their utility in predicting reef management impacts.

Phi-Space ST identifies continuous cell states in spatial transcriptomics data using scRNA-seq references, revealing niche-specific cell types and patterns in cancer tissues.

This paper reviews multivariate methods for integrating histological images and gene expression data, showing they capture distinct yet complementary aspects of the underlying information.

phylobar provides an R package for interactive multiresolution compositional barplots to visualize hierarchical omics data, enabling exploration across taxonomic resolutions.

This study integrates multi-omic data from Staphylococcus aureus exposed to human serum to identify genetic factors critical for survival, revealing interconnected metabolic, iron transport, and stress response mechanisms.

tensorOmics integrates longitudinal multi-omics data using tensor factorisation to capture coordinated molecular responses across time and omic layers.

This paper introduces an R-based workflow for integrating microbial multi-omics data, enabling analysis of transcriptomic, proteomic, and metabolomic datasets and generating pathway-level insights.

The paper identifies seven macrophage subtypes in the human inner ear across development and adulthood using scRNA-seq data, linking them to specific developmental stages and gene expression profiles.

CellDiffusion enhances single-cell and spatial RNA-seq annotation by generating virtual cells to bridge the gap with bulk RNA-seq references, improving accuracy and revealing new biological insights.

PLSKO is a knockoff generator that controls FDR in omics variable selection, showing robustness across RNA-seq, proteomics, metabolomics, and microbiome data.

This study shows that hypomethylating agents induce epigenetic and transcriptional heterogeneity in AML cells, with some cells retaining methylation and showing increased self-renewal, and identifies statins as a potential co-treatment to enhance HMA efficacy.

This study integrates miRNomic and lipidomic analysis of plasma extracellular vesicles from AUD patients and controls to identify sex-based molecular signatures and their functional implications.

The paper identifies distinct microbial patterns and clusters associated with varying oral mucositis severity trajectories in head and neck cancer patients.

NeighbourNet constructs cell-specific co-expression networks to uncover regulatory patterns in single-cell data, improving efficiency and enabling downstream analysis.

This paper introduces FS-PLS, a feature selection method that generates minimal disease signatures from omics data without requiring library size normalization, achieving smaller and comparable performance to existing methods.

This paper introduces LUPINE, a method for inferring microbial networks in longitudinal studies, and validates it using simulated data and case studies.

The paper integrates metagenomic and climatic data to model global picoplankton biogeography, identifying ten distinct groups and their environmental and functional features.

This paper reviews simulation methods for microbiome data analysis, demonstrating their use in benchmarking, power analysis, and evaluating key properties of simulated data.

StableMate identifies stable predictors across omics datasets to improve reproducibility and interpretability of biological associations.

Phi-Space continuously phenotypes single-cell multi-omics data by embedding cells in a low-dimensional space defined by reference phenotypes, enabling robust annotation and analysis of transitional and novel cell states.

Metaphor is a fully-automated workflow for genome-resolved metagenomics that improves genome binning quality through flexible assembly strategies and combined binning algorithms.

Sincast projects single cell RNA-seq data onto bulk reference atlases to predict cell identities without batch correction, highlighting new cell states.

The paper presents a framework for integrating longitudinal multi-omics data to detect temporal relationships and interactions between omics layers, applied to cell cycle and aphid feeding studies.

constclust identifies robust cell clusters in scRNA-seq data by reconciling clustering results across parameter variations, improving accuracy and reproducibility with lower computational cost.

This paper introduces a multivariate batch correction method for microbiome data, showing it effectively removes batch effects while preserving treatment variation.

The paper integrates hundreds of transcriptome datasets from multiple platforms to create a cross-platform blood cell atlas, enabling robust cell type clustering without batch correction.

The paper analyzes myeloid cells from various sources to identify gaps in in vitro models compared to in vivo biology.