Rydén Martin, Englund Martin, Ali Neserin
Department of Clinical Sciences Lund, Orthopedics, Clinical Epidemiology Unit, Lund University, SE-22185 Lund, Sweden.
Department of Clinical Sciences Lund, Rheumatology and Molecular Skeletal Biology, Lund University, SE-22184 Lund, Sweden.
Bioinformatics. 2021 Oct 25;37(20):3491-3493. doi: 10.1093/bioinformatics/btab373.
Functional analysis has become a common approach to incorporate biological knowledge into the analysis of omics data, and to explore molecular events that govern a disease state. It is though only one step in a wider analytical pipeline that typically requires use of multiple individual analysis software. There is currently a need for a well-integrated omics analysis tool that performs all the steps. The ProteoMill portal is developed as an R Shiny application and integrates all necessary steps from data-upload, converting identifiers, to quality control, differential expression and network-based functional analysis into a single fast, interactive easy to use workflow. Further, it maintains annotation data sources up to date, overcoming a common problem with use of outdated information and seamlessly integrates multiple R-packages for an improved user-experience. The functionality provided in this software can benefit researchers by facilitating the exploratory analysis of proteomics data.
ProteoMill is available at https://proteomill.com.
功能分析已成为将生物学知识纳入组学数据分析并探索控制疾病状态的分子事件的常用方法。不过，它只是更广泛分析流程中的一步，该流程通常需要使用多个单独的分析软件。目前需要一个执行所有步骤的集成良好的组学分析工具。ProteoMill门户是作为一个R Shiny应用程序开发的，它将从数据上传、标识符转换到质量控制、差异表达和基于网络的功能分析等所有必要步骤集成到一个快速、交互式且易于使用的工作流程中。此外，它能保持注释数据源的最新状态，克服了使用过时信息的常见问题，并无缝集成多个R包以改善用户体验。该软件提供的功能可通过促进蛋白质组学数据的探索性分析使研究人员受益。
ProteoMill可在https://proteomill.com获取。
