Summary: Cytoscape.js is an open-source JavaScript-based graph library. Its most common use case is as a visualization software component, so it can be used to render interactive graphs in a web browser. It also can be used in a headless manner, useful for graph operations on a server, such as Node.js.Availability and implementation: Cytoscape.js is implemented in JavaScript. Documentation, downloads and source code are available at http://js.cytoscape.org.Contact: gary.bader@utoronto.ca

A rapidly growing corpus of formal, computable pathway information can be used to answer important biological questions including finding non-trivial connections between cellular processes, identifying significantly altered portions of the cellular network in a disease state and building predictive models that can be used for precision medicine. Due to its complexity and fragmented nature, however, working with pathway data is still difficult. We present Paxtools, a Java library that contains algorithms, software components and converters for biological pathways represented in the standard BioPAX language. Paxtools allows scientists to focus on their scientific problem by removing technical barriers to access and analyse pathway information. Paxtools can run on any platform that has a Java Runtime Environment and was tested on most modern operating systems. Paxtools is open source and is available under the Lesser GNU public license (LGPL), which allows users to freely use the code in their software systems with a requirement for attribution. Source code for the current release (4.2.0) can be found in Software S1. A detailed manual for obtaining and using Paxtools can be found in Protocol S1. The latest sources and release bundles can be obtained from biopax.org/paxtools.

The cBioPortal for Cancer Genomics provides intuitive visualization and analysis of complex cancer genomics data. The public site (http://cbioportal.org/) is accessed by more than 1,500 researchers per day, and there are now dozens of local instances of the software that host private data sets at cancer centers around the globe. We have recently released the software under an open source license, making it free to use and modify by anybody. The software and detailed documentation are available at https://github.com/cBioPortal/cbioportal. We are now establishing a multi-institutional software development network, which will coordinate and drive the future development of the software and associated data pipelines. This group will focus on four main areas: 1. New analysis and visualization features, including: a. Improved support for cross-cancer queries and cohort comparisons. b. Enhanced clinical decision support for precision oncology, including an improved patient view with knowledge base integration, patient timelines and improved tools for visualizing tumor evolution. 2. New data pipelines, including support for new genomic data types and streamlined pipelines for TCGA and the International Cancer Genome Consortium (ICGC). 3. Software architecture and performance improvements. 4. Community engagement: Documentation, user support, and training. This coordinated effort will help to further establish the cBioPortal as the software of choice in cancer genomics research, both in academia and the pharmaceutical industry. Furthermore, as the sequencing of tumor samples has entered clinical practice, we are expanding the features of the software so that it can be used for precision medicine at cancer centers. In particular, clean, web-accessible, interactive clinical reports integrating multiple sources of genome variation and clinical annotation over time has potential to improve clinical action beyond current text-based molecular reports. By making complex genomic data easily interpretable and linking it to information about drugs and clinical trials, the cBioPortal software has the potential to facilitate the use of genomic data in clinical decision making. Citation Format: Jianjiong Gao, James Lindsay, Stuart Watt, Istemi Bahceci, Pieter Lukasse, Adam Abeshouse, Hsiao-Wei Chen, Ino de Bruijn, Benjamin Gross, Dong Li, Ritika Kundra, Zachary Heins, Jorge Reis-Filho, Onur Sumer, Yichao Sun, Jiaojiao Wang, Qingguo Wang, Hongxin Zhang, Priti Kumari, M. Furkan Sahin, Sander de Ridder, Fedde Schaeffer, Kees van Bochove, Ugur Dogrusoz, Trevor Pugh, Chris Sander, Ethan Cerami, Nikolaus Schultz. The cBioPortal for cancer genomics and its application in precision oncology. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 5277.

Summary Cytoscape.js is an open-source JavaScript-based graph library. Its most common use case is as a visualisation software component, so it can be used to render interactive graphs in a web browser. It also can be used in a headless manner, useful for graph operations on a server, such as Node.js. This update describes new features and enhancements introduced over many new versions from 2015 to 2022. Availability Cytoscape.js is implemented in JavaScript. Documentation, downloads and source code are available at http://js.cytoscape.org. Supplementary information Supplementary data are available at Bioinformatics online.