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This package helps to construct confidence matrices for Hi-C replicates

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HiConfidence

This package helps to construct confidence matrices for Hi-C replicates

Usage

  1. Generate Confidence matrix for the pair of replicates:
calculate_confidence(Hi-C_matrix_rep1,Hi-C_matrix_rep2,k_parameter)
  1. Choose the best parameter k based on correlation of IS with window_size:
choose_k(Hi-C_reps_file_names)
  1. Construct chromatin profile in the area around averaged TADs boundary using correction for replicates' confidence:
average_tad(Hi-C_reps_file_names, k_parameter, tads_positions, area_size)
  1. Generate Hi-C maps in lower resolution using correction for replicates' confidence:
downsampling(Hi-C_reps_file_names, k_parameter, factor, output_file_name)

See test_example.py for more examples.

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This package helps to construct confidence matrices for Hi-C replicates

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