<｜begin▁of▁sentence｜>### Instruction:
Given the American College Football network graph which you can read from a GML file named football.gml, can you use the Markov clustering algorithm in cdlib to perform community detection with an expansion factor of 2, inflation factor of 2, initial loop value of 1, a maximum of 100 iterations, a pruning threshold of 0.001, pruning to be performed every 2 iterations, and convergence checked every 2 iterations? And can you export the resulting clustering into a JSON representation?
### Response:
import networkx as nx
from cdlib import algorithms

# Read the graph
G = nx.read_gml('football.gml')

# Perform Markov Clustering
coms = algorithms.markov_clustering(G, expansion=2, inflation=2, loop_value=1, iterations=100, pruning_threshold=0.001, pruning_frequency=2, convergence_check_frequency=2)

# Generate a JSON representation of the clustering
json_coms = coms.to_json()

print(json_coms)
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