Computational Biology, Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA.
Data Core, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA.
Bioinformatics. 2023 Oct 3;39(10). doi: 10.1093/bioinformatics/btad583.
We present the phippery software suite for analyzing data from phage display methods that use immunoprecipitation and deep sequencing to capture antibody binding to peptides, often referred to as PhIP-Seq. It has three main components that can be used separately or in conjunction: (i) a Nextflow pipeline, phip-flow, to process raw sequencing data into a compact, multidimensional dataset format and allows for end-to-end automation of reproducible workflows. (ii) a Python API, phippery, which provides interfaces for tasks such as count normalization, enrichment calculation, multidimensional scaling, and more, and (iii) a Streamlit application, phip-viz, as an interactive interface for visualizing the data as a heatmap in a flexible manner.
All software packages are publicly available under the MIT License. The phip-flow pipeline: https://github.com/matsengrp/phip-flow. The phippery library: https://github.com/matsengrp/phippery. The phip-viz Streamlit application: https://github.com/matsengrp/phip-viz.
我们介绍了 phippery 软件套件，用于分析使用免疫沉淀和深度测序来捕获抗体与肽结合的噬菌体展示方法的数据，通常称为 PhIP-Seq。它有三个主要组件，可以单独使用或结合使用：（i）一个 Nextflow 管道 phip-flow，用于将原始测序数据处理成紧凑的多维数据集格式，并允许可重复工作流程的端到端自动化。（ii）一个 Python API phippery，它提供了诸如计数归一化、富集计算、多维缩放等任务的接口，以及（iii）一个 Streamlit 应用程序 phip-viz，作为一种灵活的热图可视化数据的交互界面。
所有软件包均根据 MIT 许可证公开提供。phip-flow 管道：https://github.com/matsengrp/phip-flow。phippery 库：https://github.com/matsengrp/phippery。phip-viz Streamlit 应用程序：https://github.com/matsengrp/phip-viz。
