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57d3d9e78b
Build pipeline: openpipelines-bio.openpipeline-qc.0.1.1-976qz
Source commit: f9c63d1286
Source message: bump version to v0.1.1
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4.3 KiB
Markdown
53 lines
4.3 KiB
Markdown
# OpenPipeline QC
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OpenPipeline QC contains an extensible workflow for the generation of a stand-alone, interactive ingestion QC report for single-cell and spatial omics data. It is part of the [OpenPipeline](https://github.com/openpipelines-bio/openpipeline/) ecosystem and extends it with specialized functionality for ingestion quality control.
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[](https://www.viash-hub.com/packages/openpipeline_qc)
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[](https://github.com/openpipelines-bio/openpipeline_qc)
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[](https://github.com/openpipelines-bio/openpipeline_qc/blob/main/LICENSE)
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[](https://github.com/openpipelines-bio/openpipeline_qc/issues)
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[](https://viash.io)
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## Functionality
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### 1. QC Metrics Calculation
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The workflow calculates extensive ingestion QC metrics at both the observation and feature levels. **Observation-level metrics** include total counts per cell, gene detection rates, mitochondrial and ribosomal gene percentages, and expression concentration in top genes. **Feature-level metrics** cover gene expression summaries such as total counts per gene, detection rates across cells, mean expression levels, and dropout percentages.
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**Spatial data metrics:**
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For spatial data, the workflow also surfaces segmentation metrics.
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### 2. Interactive Report Generation
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After calculating QC metrics, the workflow generates a standalone interactive report using the [siqc](https://github.com/openpipelines-bio/siqc) package (standalone, interactive QC reporting engine).
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**siqc features:**
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- 🚀 **Progressive Loading**: Large datasets (millions of cells) load incrementally without blocking the UI
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- 📊 **Interactive Visualizations**: Histograms, scatter plots, heatmaps, and spatial plots with Plotly.js
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- 🗜️ **Efficient Compression**: Binary data format with gzip compression for optimal file sizes
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- 📄 **Standalone Reports**: Single HTML file with no external dependencies
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- 🎯 **Spatial Analysis**: Advanced spatial plotting with faceting and optimization
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- ⚡ **Performance Optimized**: Web Workers, typed arrays, and multi-scale rendering
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### 3. Quality Assessment for Downstream Processing
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The generated report can be used to set thresholds for QC-based filtering, which can then be applied for further processing of the data using the core [OpenPipeline](https://github.com/openpipelines-bio/openpipeline/) of [OpenPipeline Spatial](https://github.com/openpipelines-bio/openpipeline_spatial/) packages.
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**Supported platforms:**
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- 10x Genomics single-cell multi-omics (Cellranger Multi output)
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- 10x Genomics Xenium spatial transcriptomics
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## Execution via CLI or Seqera Cloud
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The openpipeline_qc package is available via [Viash Hub](https://www.viash-hub.com/packages/openpipeline_qc/latest/), where you can receive instructions on how to run the end-to-end workflow as well as individual subworkflows or components.
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It's possible to run the workflow directly from Seqera Cloud. The necessary Nextflow schema files have been [built and provided with the workflows](https://packages.viash-hub.com/vsh/openpipeline_qc/-/tree/build/main/target/nextflow/workflows/generate_qc_report) in order to use the form-based input. However, Seqera Cloud can not deal with multiple-value parameters for batch processing of multiple samples. Therefore, it's better to use Viash Hub also here for launching the workflow on Seqera Cloud.
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* Navigate to the [Viash Hub package page](https://www.viash-hub.com/packages/openpipeline_qc/latest/), select the workflow you want to launch and click the `launch` button.
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* Select the execution environment of choice (e.g. `Seqera Cloud`, `Nextflow` or `Executable`)
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* Fill in the form with the required parameters and launch the workflow.
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## Support
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For issues specific to quality control analysis, please use the [GitHub issues tracker](https://github.com/openpipelines-bio/openpipeline_qc/issues). For general OpenPipeline questions, refer to the main [OpenPipeline documentation](https://openpipelines.bio/).
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