plothic 0.4.16

Plot Whole genome Hi-C contact matrix heatmap

PlotHiC

PlotHiC is used to visualize global interaction heatmaps after genome scaffolding.

If you have any questions, please Open Issues or provide us with your comments via the email below.

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Content

• PlotHiC
  • Content
  • Installation
    • pip
  • Usage
    • Input file
    • example
    • other parameter
    • Color map
  • Citations

Installation

• Dependency : python = "^3.10"

pip

# pip install 
pip install plothic

Usage

Input file

• genome.hic

This file is taken directly from 3d-dna, you need to select the final hic file (which has already been error adjusted and chromosome boundaries determined).

• chr.tx

1. This file is used for heatmap labeling. The first column is the name of the chromosome.
2. The second column is the length of the chromosome (this length is the length of the hic file in Juicebox and can be manually determined from Juicebox).
3. The third column is the order in which the chromosomes are placed, which is used to customize the arrangement of chromosomes (for example, from max to min).

Note: the length is in .hic file, not true base length.

# name length index
Chr1 24800000 5
Chr2 44380000 4
Chr3 63338000 3
Chr4 81187000 2
Chr5 97650000 1

example

• Default order

plothic -hic genome.hic -chr chr.txt -r 100000

# -hic > .hic file 
# -chr > chromosome length (in .hic file)
# -r > resolution to visualization

• Custom order

plothic -hic genome.hic -chr chr.txt -r 100000 --order

# -hic > .hic file 
# -chr > chromosome length (in .hic file)
# -r > resolution to visualization
# --order > 

other parameter

Color map

PlotHiC uses YlOrRd by default, you can choose more colors from Matplotlib.

Citations

If you used PlotHiC in your research, please cite us:

Zijie Jiang, Zhixiang Peng, Zhaoyuan Wei, Jiahe Sun, Yongjiang Luo, Lingzi Bie, Guoqing Zhang, Yi Wang, A deep learning-based method enables the automatic and accurate assembly of chromosome-level genomes, Nucleic Acids Research, 2024;, gkae789, https://doi.org/10.1093/nar/gkae789