# Multiomics Result Result #90 — Analysis Report

Generated 2026-09-21 02:39:17 · 1 run(s) · CAT-G Data Analyzer

## 1. snf (#90)

2026-09-21 02:18:32 · multiomics_result · status: completed

*SNF fused the views into 3 sample clusters.*

### snf cluster sizes

| Cluster | Samples |
|---|---|
| 0 | 9 |
| 1 | 7 |
| 2 | 4 |

![snf network](data:image/png;base64,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)

*snf network*

### Method & Provenance

- **Method:** Multi-omics — Similarity Network Fusion
- **Engine:** Python · snfpy + scikit-learn (spectral clustering) 1.8.0
- **Input datasets:** gallery — example_metabolomics.csv
- **Started:** 2026-09-21 02:18:32.756378
- **Permanent link:** https://cat-g-omxpert.wishartlab.com/multiomics/results/by-token/c8e4d8c8f32e4a5a927692fe03422ae9

| Parameter | Value |
|---|---|
| dataset_ids | — |
| pipeline_type | snf |

**Command history**

```python
import snf
```

```python
fused = snf.snf(affinity_matrices)
```

```python
labels = sklearn.cluster.SpectralClustering(n_clusters=3).fit_predict(fused)
```
