Obstetrics and Gynecology Hospital, Institute of Reproduction and Development, Fudan University, Shanghai, China.
Shanghai Key Laboratory of Reproduction and Development, Shanghai, China.
Methods Mol Biol. 2025;2856:197-212. doi: 10.1007/978-1-0716-4136-1_11.
Peakachu is a supervised-learning-based approach that identifies chromatin loops from chromatin contact data. Here, we present Peakachu version 2, an updated version that significantly improves extensibility, usability, and computational efficiency compared to its predecessor. It features pretrained models tailored for a wide range of experimental platforms, such as Hi-C, Micro-C, ChIA-PET, HiChIP, HiCAR, and TrAC-loop. This chapter offers a step-by-step tutorial guiding users through the process of training Peakachu models from scratch and utilizing pretrained models to predict chromatin loops across various platforms.
Peakachu 是一种基于监督学习的方法，可从染色质接触数据中识别染色质环。在这里，我们介绍 Peakachu 版本 2，与前代相比，它在可扩展性、可用性和计算效率方面有了显著的提升。它具有针对各种实验平台（如 Hi-C、Micro-C、ChIA-PET、HiChIP、HiCAR 和 TrAC-loop）定制的预训练模型。本章提供了一个逐步的教程，指导用户从头开始训练 Peakachu 模型，并利用预训练模型在各种平台上预测染色质环。
