Orchestrating a community-developed computational workshop and accompanying training materials [version 1; referees: 2 approved]

The importance of bioinformatics, computational biology, and data science in biomedical research continues to grow, driving a need for effective instruction and education. A workshop setting, with lectures and guided hands-on tutorials, is a common approach to teaching practical computational and analytical methods. Here, we detail the process we used to produce high-quality, community-authored educational materials that are available for public consumption and reuse. The coordinated efforts of 17 authors over 10 weeks resulted in 15 workshops available as a website and as a 388-page electronic book. We describe how we utilized cloud infrastructure, GitHub, and a literate programming approach to robustly deliver hands-on tutorials to participants of the annual Bioconductor conference. The scripts, raw and published workshop materials, and cloud machine image are all openly available. Our approach uses free services and software and can be adapted by workshop organizers and authors in other contests with appropriate technical backgrounds

The rockerverse : packages and applications for containerisation with R

The Rocker Project provides widely used Docker images for R across different application scenarios. This article surveys downstream projects that build upon the Rocker Project images and presents the current state of R packages for managing Docker images and controlling containers. These use cases cover diverse topics such as package development, reproducible research, collaborative work, cloud-based data processing, and production deployment of services. The variety of applications demonstrates the power of the Rocker Project specifically and containerisation in general. Across the diverse ways to use containers, we identified common themes: reproducible environments, scalability and efficiency, and portability across clouds. We conclude that the current growth and diversification of use cases is likely to continue its positive impact, but see the need for consolidating the Rockerverse ecosystem of packages, developing common practices for applications, and exploring alternative containerisation software

Inverting the model of genomics data sharing with the NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space

The NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL; https://anvilproject.org) was developed to address a widespread community need for a unified computing environment for genomics data storage, management, and analysis. In this perspective, we present AnVIL, describe its ecosystem and interoperability with other platforms, and highlight how this platform and associated initiatives contribute to improved genomic data sharing efforts. The AnVIL is a federated cloud platform designed to manage and store genomics and related data, enable population-scale analysis, and facilitate collaboration through the sharing of data, code, and analysis results. By inverting the traditional model of data sharing, the AnVIL eliminates the need for data movement while also adding security measures for active threat detection and monitoring and provides scalable, shared computing resources for any researcher. We describe the core data management and analysis components of the AnVIL, which currently consists of Terra, Gen3, Galaxy, RStudio/Bioconductor, Dockstore, and Jupyter, and describe several flagship genomics datasets available within the AnVIL. We continue to extend and innovate the AnVIL ecosystem by implementing new capabilities, including mechanisms for interoperability and responsible data sharing, while streamlining access management. The AnVIL opens many new opportunities for analysis, collaboration, and data sharing that are needed to drive research and to make discoveries through the joint analysis of hundreds of thousands to millions of genomes along with associated clinical and molecular data types

smped/extraChIPs: RELEASE_3_18

<p>Archived source code from v1.6.0, as released with Bioconductor 3.18</p&gt

Wenjun-Liu/sSNAPPY: V1.6.1

<p>sSNAPPY version 1.6.1 that was available as part of Bioconductor release 3.18.</p&gt

phenomecentre/peakPantheR: Bioc 3.18 release version (v1.16.0)

<p>This update mirrors the Bioconductor 3.18 release version (v1.16.0) News:</p> <ul> <li>corrections in vignettes</li> <li>ROI, uROI and FIR input checks for <code>NA</code> in rtMin, rtMax, mzMin and mzMax</li> <li>correct <code>plotAnnotationDiagnosticMultiplot</code> axes limit after change in ggplot2 behaviour following a rotation</li> </ul&gt

phenomecentre/peakPantheR: Bioc 3.18 release version (v1.16.0)

<p>This update mirrors the Bioconductor 3.18 release version (v1.16.0) News:</p> <ul> <li>corrections in vignettes</li> <li>ROI, uROI and FIR input checks for <code>NA</code> in rtMin, rtMax, mzMin and mzMax</li> <li>correct <code>plotAnnotationDiagnosticMultiplot</code> axes limit after change in ggplot2 behaviour following a rotation</li> </ul&gt