STRING protein interaction analysis with omicverse

Overview

Invoke this skill when the user has a list of genes and wants to explore STRING protein–protein interactions via omicverse. The workflow mirrors t_network.ipynb, covering species selection, S TRING API queries, and quick visualisation of the resulting network.

Instructions

1. Set up libraries
   • Import omicverse as ov and call ov.utils.ov_plot_set() (or ov.plot_set()) to match omicverse aesthetics.
2. Collect gene inputs
   • Accept a curated list of gene symbols (gene_list = [...]).
   • Encourage the user to flag priority genes or categories so you can colour-code groups in the plot.
3. Assign metadata for plotting
   • Build dictionaries mapping genes to types and colours, e.g. gene_type_dict = dict(zip(gene_list, ['Type1']*5 + ['Type2']*6 )) and gene_color_dict = {...}.
   • Remind users that consistent group labels improve legend readability.
4. Query STRING interactions
   • Call ov.bulk.string_interaction(gene_list, species_id) where species_id is the NCBI taxonomy ID (e.g. 4932 for yeast).
   • Inspect the resulting DataFrame for combined scores and evidence channels to verify coverage.
5. Construct the network object
   • Initialise ppi = ov.bulk.pyPPI(gene=gene_list, gene_type_dict=..., gene_color_dict=..., species=species_id).
   • Run ppi.interaction_analysis() to fetch and cache STRING edges.
6. Visualise the network
   • Generate a default plot with ppi.plot_network() to reproduce the notebook figure.
   • Mention that advanced styling (layout, node size, legends) can be tuned through ov.utils.plot_network keyword arguments if the user requests adjustments.
7. Troubleshooting
   • Ensure gene symbols match the species—STRING expects case-sensitive identifiers; suggest mapping Ensembl IDs to symbols when queries fail.
   • If the API rate-limits, instruct the user to wait or provide a cached interaction table.
   • For missing interactions, recommend enabling STRING's "add_nodes" option via ppi.interaction_analysis(add_nodes=...) to exp and the network.

Examples

• "Retrieve STRING interactions for FAA4 and plot the network highlighting two gene classes."
• "Download the STRING edge table for my Saccharomyces cerevisiae gene panel and colour nodes by module."
• "Extend the network by adding the top five predicted partners before plotting."

References

• Tutorial notebook: t_network.ipynb
• STRING background: string-db.org
• Quick copy/paste commands: reference.md

Referenced Files

The following files are referenced in this skill and included for context.

reference.md

# STRING PPI quick commands

```python
import omicverse as ov

ov.utils.ov_plot_set()

gene_list = ['FAA4', 'POX1', 'FAT1', 'FAS2', 'FAS1', 'FAA1', 'OLE1', 'YJU3', 'TGL3', 'INA1', 'TGL5']

gene_type_dict = dict(zip(gene_list, ['Type1'] * 5 + ['Type2'] * 6))
gene_color_dict = dict(zip(gene_list, ['#F7828A'] * 5 + ['#9CCCA4'] * 6))

G_res = ov.bulk.string_interaction(gene_list, 4932)
print(G_res.head())

ppi = ov.bulk.pyPPI(gene=gene_list,
                    gene_type_dict=gene_type_dict,
                    gene_color_dict=gene_color_dict,
                    species=4932)
ppi.interaction_analysis()
ppi.plot_network()