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.
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)
HiCAT-human is a tool to automatically annotate centromere HOR patterns from both reads and assemblies of multiple human samples.
#install
git clone https://github.com/xjtu-omics/HiCAT-human.git
conda install -y --file requirements.txt
cd ./stringdecomposer && make
HiCAT-human consists of 4 modules:
readsused for reads HOR annotation.reads_aggregateused for aggregating reads annotation results.assemblyused for assembly HOR annotation.assembly_matchused for matching assembly annotation results to reads annotation results.
- 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.
If you have any questions, please feel free to contact: [email protected], [email protected], [email protected]
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