<｜begin▁of▁sentence｜>### Instruction:
Given a dataset of 32 mouse connectomes with distinct genotypes and various metrics, how can one compute the average clustering coefficient of the largest connected component in the brain network of the first mouse in the dataset?
### Response:
import networkx as nx
from graspologic.datasets import load_mice

# Load mouse connectome data
mouse_data = load_mice()

# Example usage - Construct networkx graph from the first adjacency matrix
adjacency_matrix = mouse_data.graphs[0]
G = nx.from_numpy_matrix(adjacency_matrix)

# Compute the largest connected component
largest_cc = max(nx.connected_components(G), key=len)
largest_subgraph = G.subgraph(largest_cc).copy()

# Analysis - Example: Calculate the average clustering coefficient for the largest subgraph
avg_clustering_coefficient = nx.average_clustering(largest_subgraph)
print(f'Average Clustering Coefficient: {avg_clustering_coefficient}')
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