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DOI

HiCAT-human

We proposed a modified version of our previous HOR annotation tool HiCAT for automatically annotating centromere HOR patterns from both HiFi reads and assemblies of multiple human samples.

Dependencies

Python 3.9.13

Development environment: Linux

Development tool: Pycharm

Packages Version
biopython 1.79
joblib 1.1.0
lastz 1.04.22
matplotlib 3.5.1
numpy 1.22.3
pandas 1.4.0
python-edlib 1.3.9
python-levenshtein 0.12.2
scikit-learn 1.0.2
seqtk 1.2
setuptools 61.2.0

StringDecomposer version 1.1.2. (included in HiCAT-human source code)

Quick start

HiCAT-human is a tool to automatically annotate centromere HOR patterns from both reads and assemblies of multiple human samples.

Installation

#install
git clone https://github.com/xjtu-omics/HiCAT-human.git
conda install -y --file requirements.txt
cd ./stringdecomposer && make

Overview

HiCAT-human consists of 4 modules:

  • reads used for reads HOR annotation.
  • reads_aggregate used for aggregating reads annotation results.
  • assembly used for assembly HOR annotation.
  • assembly_match used for matching assembly annotation results to reads annotation results.

Input data

  • Reads HOR annotation: whole genome HiFi reads.
  • Assembly HOR annotation: haplotype-resolved human genome.

For detail usage, read the docs on the HiCAT-human wiki.

Contact

If you have any questions, please feel free to contact: [email protected], [email protected], [email protected]

Reference

Please cite the following paper when you use HiCAT-human in your work

Gao S, Zhang Y, Bush SJ, Wang B, Yang X, Ye K. Centromere landscapes resolved from hundreds of human genomes. Genomics, Proteomics & Bioinformatics. 2024 Oct 18:qzae071. https://doi.org/10.1093/gpbjnl/qzae071

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