tucca-rna-seq - v0.9.0

Release v0.9.0

[!WARNING] This workflow is still under construction. Release v0.9.0 marks our first public release. v0.9.0 contains all logic to process raw paired-end RNA-Seq reads through differential expression. We encourage users to test this release and provide feedback, but please be aware that users should expect our documentation to be incomplete and to have major reworks until v1.0.0 is released. Please open an issue to report any bugs or suggest improvements. Additionally, feel free to contact us with any questions.

This release marks a significant milestone for the tucca-cellag/tucca-rna-seq workflow! We are thrilled to announce v0.9.0, a feature-rich and stable pre-release that paves the way for our upcoming v1.0.0 launch.

This version solidifies the core analysis pipeline, providing a robust, reproducible, and user-friendly experience for RNA-Seq analysis in cellular agriculture research.

Key Features in this Release:

• Comprehensive RNA-Seq Analysis: A complete pipeline from raw sequencing reads (FASTQ) or SRA accessions to differential gene expression analysis.
• Flexible & Reproducible Execution: Extensive support for conda, singularity, and apptainer ensures that the workflow is portable and results are reproducible across different computing environments.
• Robust Data Handling: Seamlessly processes data from public repositories (SRA) or local files and supports reference genomes from both Ensembl and RefSeq.
• Powerful Differential Expression: Leverages tximeta for intelligent transcript-to-gene summarization and DESeq2 for sophisticated differential expression analysis, with highly customizable configurations.
• Rigorous Quality Control: Integrates a suite of quality control tools, including FastQC, Qualimap, and MultiQC, to ensure data integrity and provide comprehensive summary reports.
• Automated Testing: The workflow is continuously validated through a rigorous suite of automated tests on GitHub Actions, ensuring reliability and stability.

Looking Ahead: v1.0.0 and Interactive Analysis

The next stop is v1.0.0!

Currently, the workflow can generate a large number of DESeq2 result files, especially for experiments with multiple conditions and contrasts. While this is thorough, we recognize that navigating dozens of individual result files can be challenging.

The centerpiece of the v1.0.0 release will be an interactive analysis toolkit that allows you to dynamically explore and visualize your results. This will include a suite of Shiny applications leveraging powerful packages like pcaExplorer, ideal, and GeneTonic to bring your data to life, as well as custom scripting to generate our favorite clusterProfiler figures.

We encourage you to test this v0.9.0 release and provide feedback. Please open an issue to report any bugs or suggest improvements.

Thank you for your support and happy analyzing!

- Python
Published by benjibromberg 9 months ago

tucca-rna-seq - v0.9.0

Release v0.9.0

This release marks a significant milestone for the tucca-cellag/tucca-rna-seq workflow! We are thrilled to announce v0.9.0, a feature-rich and stable pre-release that paves the way for our upcoming v1.0.0 launch.

This version solidifies the core analysis pipeline, providing a robust, reproducible, and user-friendly experience for RNA-Seq analysis in cellular agriculture research.

Key Features in this Release:

• Comprehensive RNA-Seq Analysis: A complete pipeline from raw sequencing reads (FASTQ) or SRA accessions to differential gene expression analysis.
• Flexible & Reproducible Execution: Extensive support for conda, singularity, and apptainer ensures that the workflow is portable and results are reproducible across different computing environments.
• Robust Data Handling: Seamlessly processes data from public repositories (SRA) or local files and supports reference genomes from both Ensembl and RefSeq.
• Powerful Differential Expression: Leverages tximeta for intelligent transcript-to-gene summarization and DESeq2 for sophisticated differential expression analysis, with highly customizable configurations.
• Rigorous Quality Control: Integrates a suite of quality control tools, including FastQC, Qualimap, and MultiQC, to ensure data integrity and provide comprehensive summary reports.
• Automated Testing: The workflow is continuously validated through a rigorous suite of automated tests on GitHub Actions, ensuring reliability and stability.

Looking Ahead: v1.0.0 and Interactive Analysis

The next and final stop is v1.0.0!

Currently, the workflow can generate a large number of DESeq2 result files, especially for experiments with multiple conditions and contrasts. While this is thorough, we recognize that navigating dozens of individual result files can be challenging.

The centerpiece of the v1.0.0 release will be an interactive analysis toolkit that allows you to dynamically explore and visualize your results. This will include a suite of Shiny applications leveraging powerful packages like pcaExplorer, ideal, and GeneTonic to bring your data to life.

We encourage users to test this v0.9.0 release and provide feedback. Please open an issue to report any bugs or suggest improvements.

Thank you for your support and happy analyzing!

- Python
Published by benjibromberg 9 months ago