ArticleMethods in molecular biology (Clifton, N.J.)2023
Multivariate Analysis with the R Package mixOmics.
Article in Methods in molecular biology (Clifton, N.J.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed.
- Beyond bacilli: integrating the microbiome into the TB research agenda.Gut microbes · 2026Review
- Transcriptomic and Metabolomic Profiling Identifies a Core Gene-Metabolite Axis Driving African Swine Fever Virus Replication in the Soft Tick Ornithodoros lahorensis.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026Article
- Peripheral immune-redox signatures associate with cortical network alterations in anhedonic depression.Molecular psychiatry · 2026Article
- Metformin Modulates Systemic Lipid Remodeling after Traumatic Brain Injury.Research square · 2026Article
- Utilizing multimodal cortical parcellations to identify novel regions of the human cerebral cortex associated with substance use disorders.Molecular psychiatry · 2026Article
- CSGM: A R Package to Conduct a Robust Cross-Sectional Geometric Morphometric Analysis.American journal of biological anthropology · 2026Article
- Using multimodal cortical parcellations to identify novel regions of the human cerebral cortex associated with cognitive performance.Translational psychiatry · 2026Article
- Integrated multi-omics analysis of metabolomics and proteomics uncovers dysregulated amino acid metabolism in HCC metastasis.Frontiers in immunology · 2026Article
- Identification of key genes related to arginine metabolism in immunoglobulin A nephropathy through the combination of scRNA-seq and bulk RNA-seq data.Frontiers in immunology · 2026Article
- Article
- Bioinformatics Analysis and Validation of Potential Markers Associated with Prediction and Prognosis of Gastric Cancer.International journal of molecular sciences · 2024Review
- Gut Microbiota Ecological and Functional Modulation in Post-Stroke Recovery Patients: An Italian Study.Microorganisms · 2023Article
- Therapeutic Modulation of Cell Morphology and Phenotype of Diseased Human Cells towards a Healthier Cell State Using Lignin.Polymers · 2023Article
- Cell morphology as a biological fingerprint of chondrocyte phenotype in control and inflammatory conditions.Frontiers in immunology · 2023Article
- Motor- and cognitive-dominant functional network adaptations supporting dual-task performance in older adults.Imaging neuroscience (Cambridge, Mass.)Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The high-dimensional nature of proteomics data presents challenges for statistical analysis and biological interpretation. Multivariate analysis, combined with insightful visualization can help to reveal the underlying patterns in complex biological data. This chapter introduces the R package mixOmics which focuses on data exploration and integration. We first introduce methods for single data sets: both Principal Component Analysis, which can identify the patterns of variance present in data, and sparse Partial Least Squares Discriminant Analysis, which aims to identify variables that can classify samples into known groups. We then present integrative methods with Projection to Latent Structures and further extensions for discriminant analysis. We illustrate each technique on a breast cancer multi-omics study and provide the R code and data as online supplementary material for readers interested in reproducing these analyses.
Indexed as
Identifiers
36308696What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.