Release Note

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Release Note

Written by Mithila in

August 2026 Public Apps Gallery Updates 

Recently Released Platform Enhancements, Public Projects, and Scientific Workflows 

This month, we expanded the availability of key scientific workflows across Seven Bridges platforms, introduced new resources for single-cell data analysis, released eight nf-core Nextflow workflows on academic platforms (CGC, BDC, and CAVATICA), refreshed public imaging projects with integrated OHIF Viewer and 3D Slicer guides, and upgraded QIIME2 workflows for microbiome research and STAR-based tools for RNA-seq analysis. These updates are designed to improve reproducibility, usability, and accessibility for researchers working across genomics, imaging, and multi-omics workflows. 

Nextflow updates 

  1. Added Eightnf-core Nextflow Workflows on CGC, BDC, and CAVATICA Platforms 

To provide a consistent Public Apps Gallery experience across platforms, eight existing and optimized nf-core Nextflow workflows were published across multiple environments, including CAVATICA, CGC, BDC, and EU platforms. The workflows are listed below. 

  • chipseq 
  • mag 
  • nf-rnavar 
  • pgsc-calc 
  • rnafusion 
  • rnaseq 
  • Sarek 
  • Scrnaseq 

This release makes widely used Nextflow workflows more broadly accessible and simplifies adoption for researchers working across different Velsera ecosystems. 

  1. Enhancements to thesbpack_nf CWL app 

Several improvements were delivered to the sbpack_nf CWL App to streamline onboarding and deployment of Nextflow workflows on Seven Bridges platform. Updates include: 

  • Support for importing Nextflow workflow packages directly from GitHub repository URLs, reducing the need for manual archive uploads. 
  • Validation checks to prevent unsupported string output types during workflow packaging. 
  • Improved compatibility with EPI2ME and nf-core workflows 

Together, these updates improve workflow portability, reduce deployment errors, and simplify the packaging process for Nextflow users on the platform. 

Updated Public Imaging Projects 

  1. The Cancer Imaging Archive (TCIA) Imaging Project with OHIF Viewer

The TCIA public project was updated and integrated with an OHIF Viewer guide for the pre-segmentation QC validation workflow, supporting DICOM image review, image quality assessment, and basic measurements. It is now published as a public project across multiple environments, including CAVATICA, CGC, and BDC platforms. These updates help users more easily explore and analyze radiology imaging datasets hosted within the project. 

  1. COVID-19 Image Segmentation with Deep Learningand 3-D Slicer Visualization 

The COVID-19 Image Segmentation public project was upgraded and integrated with a 3D Slicer guide for the post-segmentation QC workflow. The upgraded project is now published as a public project across multiple environments, including CAVATICA, CGC, and BDC platforms. These changes strengthen the project’s value as a learning and reference resource for medical imaging and AI-assisted segmentation workflows. 

Single-Cell Analysis Resources 

  1. New Monocle Workflow for Single-Cell Trajectory Analysis

A standardized Monocle workflow has been developed to support scalable and reproducible single-cell RNA-seq trajectory analysis across platforms. The workflow enables researchers to: 

  • Reconstruct developmental and cellular trajectories. 
  • Perform pseudotime analyses. 
  • Explore branching lineage relationships. 
  • Investigate gene expression changes associated with cell state transitions. 

By providing a configurable and reusable workflow, this release simplifies advanced single-cell trajectory analysis for a broad range of biological applications.  

  1. Public Project on Monocle 3-Based Single-Cell Trajectory Inference

This public project demonstrates the reconstruction of disease-associated cellular trajectories from raw single-cell count data using the publicly available GSE253587 dataset from Bui et al. 

The resulting trajectory resolves four T-cell populations and recapitulates the major patterns reported in the original study, including a continuum from conventional T-cell states toward cycling regulatory T cells (cycTregs). Together, these results demonstrate Monocle 3’s ability to recover biologically meaningful disease-associated transitions from publicly available single-cell data. 

  1. Single-Cell RNA-seq End-to-End Analysis Public Project

A new public project on the BDC platform brings together existing single-cell analysis and visualization resources into a single end-to-end learning experience. The project is designed to: 

  • Introduce users to single-cell RNA-seq analysis workflows. 
  • Demonstrate interoperability between Seurat-based analyses and Vitessce visualizations. 
  • Showcase Human Cell Atlas datasets and related resources. 
  • Serve as a reference and onboarding environment for platform users and collaborators. 

This consolidated resource makes it easier for researchers to learn and adopt single-cell analysis workflows on the BDC platform. 

Microbiome Analysis Improvements 

8.Updated QIIME2 16S rRNA Public Workflows 

The publicly available QIIME2 workflows for microbiome analysis have been reviewed, updated, and validated to align with current platform standards. Updated workflows include: 

  • 16S rRNA Feature Classifier Training 
  • 16S rRNA Metagenomic Profiling 
  • QIIME2 Core Diversity Reporting 

Improvements include workflow validation, refreshed configurations, updated parameter guidance, enhanced documentation, and verification of referenced assets and metadata. These updates help ensure reliable execution and a more consistent user experience for microbiome researchers. 

RNA-seq Workflow Updates 

  1. Updated STAR Toolkit and RNA-seq Alignment Workflows

The STAR toolkit and associated RNA-seq alignment workflows available through the Public Apps Gallery have been updated to the latest supported version, improving consistency and maintaining alignment with current platform standards. The update includes the following components: STAR, STARsolo, STARsoloCellFiltering, STAR Genome Generate, and the RNA-seq Alignment STAR workflow. This release ensures that users performing bulk and single-cell RNA-seq analyses have access to the most up-to-date STAR-based tools while maintaining compatibility with existing analysis workflows. The refreshed toolkit supports reliable sequence alignment, genome indexing, and single-cell transcriptomic preprocessing across a variety of RNA-seq applications. 

 

Resources 

If you need help with accessing controlled study details, please contact your Velsera Seven Bridges representative or email support@velsera.com. 

 

Mithila