Multiomics Result Result #88 — Analysis Report
Contents
- cca (#88) completed
1. Cca
2026-09-21 02:18:24 · multiomics_result
The first canonical variate correlates the two views at r = 1.000.
canonical correlations
| Variate | Correlation |
|---|---|
| CV1 | 1.0 |
| CV2 | 1.0 |
| CV3 | 1.0 |
gallery — example metabolomics.csv top CV1 loadings
| Feature | CV1 loading |
|---|---|
| Protein_content | -0.092203 |
| Tryptophan | -0.004801 |
| Valine | -0.004569 |
| Serine | -0.004562 |
| Leucine | -0.002716 |
| Phenylalanine | 0.002147 |
| Threonine | 0.001742 |
| Isoleucine | -0.001573 |
| Alanine | 0.001427 |
| Proline | -0.001098 |
| Glycine | -0.000278 |
gallery — example proteomics.csv top CV1 loadings
| Feature | CV1 loading |
|---|---|
| Protein_content | -0.009469 |
| Protein_E05 | 0.0 |
| Protein_H08 | 0.0 |
| Protein_F06 | -0.0 |
| Protein_A01 | 0.0 |
| Protein_D04 | 0.0 |
| Protein_C03 | -0.0 |
| Protein_I09 | -0.0 |
| Protein_J10 | -0.0 |
| Protein_G07 | 0.0 |
| Protein_B02 | -0.0 |
cca variate scatter
cca correlation bar
cca loadings bar
Warnings
- All canonical correlations are at or near 1.0. With 20 samples and 3 components the model is almost certainly overfit; interpret the correlations as a description of this dataset only, not as evidence of real cross-omics structure.
Method & Provenance
- Method
- Multi-omics — Canonical Correlation Analysis
- Engine
- Python · statsmodels (CanCorr) 0.14.6
- Input dataset
- gallery — example_metabolomics.csv
- Started
- 2026-09-21 02:18:24.618760
- Permanent link
- https://cat-g-omxpert.wishartlab.com/multiomics/results/by-token/21244bc41b924556a8939806cdeb2457
| Parameter | Value |
|---|---|
| dataset_ids | — |
| pipeline_type | cca |
Command history
# python from statsmodels.multivariate.cancorr import CanCorr # python cca = CanCorr(X_block, Y_block).fit()