强大、可重复且灵活的自动化多组学探索性分析与报告
: robust, reproducible and flexible automated multiomics exploratory analysis and reporting.
作者信息
Blum Benjamin C, Emili Andrew
机构信息
Center for Network Systems Biology, Boston University, Boston, MA 02118, USA.
Boston University School of Medicine, Boston University, Boston, MA 02118, USA.
出版信息
Bioinform Adv. 2021 Sep 21;1(1):vbab024. doi: 10.1093/bioadv/vbab024. eCollection 2021.
SUMMARY
Mass spectrometry is an increasingly important tool for the global interrogation of diverse biomolecules. Unfortunately, the complexity of downstream data analysis is a major challenge for the routine use of these data by investigators from broader training backgrounds. Omics Notebook is an open-source framework for exploratory analysis, reporting and integrating multiomic data that are automated, reproducible and customizable. Built-in functions allow the processing of proteomic data from MaxQuant and metabolomic data from XCMS, along with other omics data in standardized input formats as specified in the documentation. In addition, the use of containerization manages R package installation requirements and is tailored for shared high-performance computing or cloud environments.
AVAILABILITY AND IMPLEMENTATION
Omics Notebook is implemented in Python and R and is available for download from https://github.com/cnsb-boston/Omics_Notebook with additional documentation under a GNU GPLv3 license.
SUPPLEMENTARY INFORMATION
Supplementary data are available at online.
摘要
质谱分析是对多种生物分子进行全面检测的一种越来越重要的工具。不幸的是，下游数据分析的复杂性对于来自更广泛培训背景的研究人员常规使用这些数据而言是一项重大挑战。组学笔记本是一个用于探索性分析、报告和整合多组学数据的开源框架，具有自动化、可重复和可定制的特点。内置功能允许处理来自MaxQuant的蛋白质组学数据和来自XCMS的代谢组学数据，以及文档中指定的标准化输入格式的其他组学数据。此外，容器化的使用管理了R包的安装要求，并针对共享高性能计算或云环境进行了定制。
可用性与实现
组学笔记本用Python和R实现，可从https://github.com/cnsb-boston/Omics_Notebook下载，并根据GNU GPLv3许可提供附加文档。
补充信息
补充数据可在网上获取。
Zotero 插件