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Seqera Documentation

website·Indexed 36 days ago

https://docs.seqera.io

Complete reference documentation for Seqera Platform, Nextflow, MultiQC, Fusion, and Wave. Includes detailed guides on the Seqera CLI and Co-Scientist, an AI assistant for bioinformatics used for code generation, pipeline development, and intelligent suggestions.

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What's inside Seqera

  2. Overview of Seqera Tower Workspaces

    Workspaces provide the operational context for launching workflow executions, defining available resources, and managing access control. They act as containers for pipelines, runs, actions, datasets, compute environments, credentials, and secrets. Access is managed via participants, collaborators, and teams.

  3. Overview of Seqera Platform Enterprise capabilities

    Seqera Platform Enterprise is a centralized environment for scientific analysis at scale, supporting both on-premises and cloud environments. It provides a suite of tools for pipeline execution, interactive analysis, data management, and AI-assisted workflow automation. Key capabilities include:

    • Pipeline Execution: Launch and monitor Nextflow pipelines via a Launchpad interface designed for non-technical users.
    • Interactive Analysis: Deploy Studios featuring JupyterLab, R-IDE, VS Code, or Xpra remote desktops.
    • Data Management: Use Data Explorer to browse AWS, Azure, and Google Cloud buckets, and Data Lineage to trace pipeline provenance.
    • Optimization: Access automated resource recommendations via pipeline optimization tools.
    • AI Integration: Utilize Co-Scientist and MCP-compatible agents for writing, debugging, and running pipelines.
    • Collaboration: Securely share data, compute, and pipelines across organizations and teams.
    • Curated Content: Access production-tested community pipelines from sources like nf-core.

  4. Overview of Seqera MCP

    Seqera MCP is a Model Context Protocol (MCP) server designed to allow AI assistants to interact directly with the Seqera ecosystem. It provides a standardized interface for AI tools to access the Seqera Platform, Wave containers, nf-core modules, and various bioinformatics data resources.

  5. Overview of Wave CLI

    Wave CLI is a command-line interface that acts as a wrapper around the Wave API. It allows developers to manage container images—specifically building, augmenting, freezing, mirroring, and scanning them—directly from a terminal. It is compatible with both hosted Wave services and self-hosted deployments and can be used interactively or integrated into CI pipelines for automation.

  6. Overview of Illumina DRAGEN for NGS secondary analysis

    Illumina DRAGEN is a platform designed for the secondary analysis of next-generation sequencing (NGS) data. It achieves high performance and speed increases over common analysis tools by combining proprietary Illumina algorithms with Field Programmable Gate Array (FPGA) hardware accelerators. On AWS, these FPGA capabilities are provided via the F1 instance type.

  7. Overview of HTSeq Count tool

    HTSeq Count is a tool within the HTSeq Python package used to process high-throughput sequencing assays. It takes aligned sequencing reads and a list of genomic features to count how many reads map to each specified feature.

  8. Overview of pipeline actions in Seqera Platform

    Pipeline actions enable event-based pipeline execution. For example, they can be used to trigger a pipeline launch via a GitHub webhook whenever a pipeline repository is updated. Use the tw actions CLI command group to manage these actions.

  9. Overview of RNA-Seq analysis workflow in Seqera Platform

    Seqera Platform supports bulk RNA sequencing (RNA-Seq) data analysis on AWS Batch compute environments. The end-to-end workflow includes:

    • Provisioning an AWS Batch compute environment for pipelines and analysis.
    • Adding and importing pipeline input data into the workspace.
    • Launching and monitoring pipeline execution.
    • Configuring custom analysis environments using Studios.
    • Managing resource allocation specifically for RNA-Seq data requirements.

  10. Overview of Google Cloud compute environments in Seqera Platform

    The Google Cloud compute environment is a public preview feature designed for running Studio sessions and small to medium-sized Nextflow pipelines. Unlike traditional batch-based environments (like Google Batch), it utilizes Google Compute Engine directly to launch a standalone instance with a local executor. The instance is automatically terminated once the execution completes.

    Key advantages over batch services include:

    • Faster Startup: Pipelines and Studio sessions typically reach a running state in under a minute by eliminating per-task VM provisioning and container pulling overhead.
    • Simplified Setup: Reduced configuration options with opinionated defaults and built-in support for Wave and Fusion.
    • Reduced Dependencies: Eliminates reliance on Google Batch APIs, requiring only core IAM permissions for Compute Engine, Cloud Storage, and IAM.

  11. Overview of QoRTs RNA-Seq analysis toolkit

    QoRTs is a toolkit used for the analysis, quality control (QC), and data management of RNA-Seq datasets. It specifically aids in detecting and identifying errors, biases, and artifacts produced by paired-end high-throughput RNA-Seq technology. It can generate count data for differential expression and differential exon usage tools, as well as genome track files for the UCSC genome browser.

  12. Overview of Fusion distributed file system

    Fusion is a virtual, lightweight, distributed file system designed to optimize data access for Nextflow data pipelines. It provides a standard POSIX interface for seamless filesystem I/O to cloud object stores, which simplifies pipeline logic and improves execution efficiency. Note that Fusion requires a license for use within Seqera Platform compute environments or directly in Nextflow.