3D genome reconstruction from partially phased Hi-C data

This repository contains files for the manuscript 3D genome reconstruction from partially phased Hi-C data (2301.11764) by Diego Cifuentes, Jan Draisma, Oskar Henriksson, Annachiara Korchmaros, Kaie Kubjas.

File descriptions

The repository contains three main parts:

• A Macualay2 script unique_identifiability_conjecture.m2, which contains the function SevenEq(nTrails) used test the unique identifiability conjecture (Conjecture 3.4 in the paper).

• A Maple script ambiguous_identifiability_proof.mpl, which does the rank computation referred to in the proof of identifiability in the fully ambiguous setting (Theorem 3.6 in the paper).

• A Julia script ambiguous_identifiability_degree.jl, which uses monodromy and certification to prove that the identifiability degree is more than 1000 for unphased data in the $\alpha=-2$ case, as well as a text file ambiguous_ID_certificates.txt that contain the certificates of 1001 certifiably distinct solutions.

• A directory reconstructions, which contains files needed for the parts of the paper that concern concrete reconstructions (Sections 4 and 5). More specifically, it contains the following subdirectories:

  • SNLC containing all the MATLAB and Julia functions needed for the reconstruction method discussed in Section 4 of the paper. In particular, this includes the MATLAB function estimate_disambiguated (for estimating unambiguous loci), the Julia function estimate_ambig_htpy (for estimating ambiguous loci with homotopy continuation), as well as the MATLAB functions estimate_ambig (for refining estimations with local optimization) and unmix_chromosomes (for the clustering step).
  • synthetic_analysiscontaining files needed for simulating and analyzing synthetic Hi-C data, including a Julia script synthetic_example.jl where these functions are used to produce Figures 3 (a)--(c) and S1 in the paper.
  • patski_analysis containing files needed for analyzing the patski dataset, including a Jupyter notebook analysis_of_patski_data.ipynb where the Figures 5, S2 and S3 are produced.
  • norm_figures that contain the full series of figures of which a sample is shown in Figure S4.

Dependencies

The MATLAB function estimate_disambiguated.m relies on ChromSDE version 2.2.