Pipeline type: CCA

CCA Results
Canonical correlations
VariateCorrelation
CV11.0000
CV21.0000
CV31.0000
gallery — example_metabolomics.csv canonical loadings
gallery — example_proteomics.csv canonical loadings
gallery — example_metabolomics.csv — top CV1 loadings
FeatureCV1 loading
Protein_content-0.0922
Tryptophan-0.0048
Valine-0.0046
Serine-0.0046
Leucine-0.0027
Phenylalanine0.0021
Threonine0.0017
Isoleucine-0.0016
Alanine0.0014
Proline-0.0011
Glycine-0.0003
gallery — example_proteomics.csv — top CV1 loadings
FeatureCV1 loading
Protein_content-0.0095
Protein_E050.0000
Protein_H080.0000
Protein_F06-0.0000
Protein_A010.0000
Protein_D040.0000
Protein_C03-0.0000
Protein_I09-0.0000
Protein_J10-0.0000
Protein_G070.0000
Protein_B02-0.0000
Figures
CCA canonical variate 1 Download PNG
CCA canonical variate 1
cca correlation bar Download PNG
cca correlation bar
cca loadings bar Download PNG
cca loadings bar

Method & Provenance

Method
Multi-omics — Canonical Correlation Analysis
Method key
cca (result type: cca, result #88)
Engine
Python · statsmodels (CanCorr) v0.14.6
Dataset(s)
#720 gallery — example_metabolomics.csv
Status
completed
Permanent link
https://cat-g-omxpert.wishartlab.com/multiomics/results/by-token/21244bc41b924556a8939806cdeb2457 Bookmark or share this URL — it does not depend on your session.
Created
2026-09-21 02:18:24.618760

Parameters used

ParameterValue
dataset_ids—
pipeline_typecca

Execution trace

Reconstructed from the parameters stored with this result — represents the Python/R calls the analysis service made.

from statsmodels.multivariate.cancorr import CanCorr
cca = CanCorr(X_block, Y_block).fit()