| Autor: |
Jonathan Rosen, Lindsay Lee, Armen Abnousi, Jiawen Chen, Jia Wen, Ming Hu, Yun Li |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Computational and Structural Biotechnology Journal, Vol 21, Iss , Pp 931-939 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2001-0370 |
| DOI: |
10.1016/j.csbj.2023.01.003 |
| Popis: |
High-throughput chromatin conformation capture technologies, such as Hi-C and Micro-C, have enabled genome-wide view of chromatin spatial organization. Most recently, Hi-C-derived enrichment-based technologies, including HiChIP and PLAC-seq, offer attractive alternatives due to their high signal-to-noise ratio and low cost. While a series of computational tools have been developed for Hi-C data, methods tailored for HiChIP and PLAC-seq data are still under development. Here we present HPTAD, a computational method to identify topologically associating domains (TADs) from HiChIP and PLAC-seq data. We performed comprehensive benchmark analysis to demonstrate its superior performance over existing TAD callers designed for Hi-C data. HPTAD is freely available at https://github.com/yunliUNC/HPTAD. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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