A Comparative Study on Approaches to Denoise Hi-C Genomic Matrices

This manuscript (permalink) was automatically generated from carlosrojas/hic_compare_manuscript@574c7e8 on April 17, 2025.

Authors

✉ — Correspondence possible via GitHub Issues or email to Fardin Haque <fardin.haque@sjsu.edu>, Carlos Rojas <carlos.rojas@sjsu.edu>.

Abstract

The architecture of the 3D genome gives rise to how cells function. These 3D genomic structures can be represented as a distances matrix. These matrices map out the interaction between genomic loci within the genome. A popular method to generate 3D genomic data is Hi-C or high-throughput chromosome conformation capture. The pipeline to map genomes to matrices is an expensive process and often results in many data samples being noisy to reduce costs. This paper will explore and compare different ways to denoise Hi-C matrices with existing image and matrix algorithms, expanding them to see their impact on genome data.

CSCSU Submission

Running HiC Tools/ Papers

CHESS Paper Info

  1. Error when running chess extract: When runnings commands in getting started, error may occur running:
chess extract \
filtered_regions_chr2_3mb_100kb.tsv \
ukm_control_fixed_le_25kb_chr2.hic \
ukm_patient_fixed_le_25kb_chr2.hic \
./features

Error:

…
venv/lib/python3.11/site-packages/chess/get_structures.py", line 124, in extract_structures
    denoise_positive = restoration.denoise_bilateral(
                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

venv/lib/python3.11/site-packages/skimage/_shared/utils.py", line 438, in fixed_func
    return func(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^
TypeError: denoise_bilateral() got an unexpected keyword argument 'multichannel'

Fix:

navigate to venv/lib/python3.11/site-packages/chess/get_structures.py Remove multichannel argument at function call at line 124: # multichannel=False

  1. Error when running chess crosscorrelate: May get error when running:
chess crosscorrelate \
features/gained_features.tsv \
filtered_regions_chr2_3mb_1mb.tsv \
./features/

Error:

venv/lib/python3.11/site-packages/chess/cross_correlation.py", line 94, in correlate2d
    kmeans = KMeans(
             ^^^^^^^
TypeError: KMeans.__init__() got an unexpected keyword argument 'precompute_distances'

Fix

navigate to venv/lib/python3.11/site-packages/chess/cross_correlation.py Remove precompute_distances parameter from constructor on line 94: # precompute_distances=True

sslHiC Paper Info

FreeHiC Paper Info