38 lines
1.8 KiB
Markdown
38 lines
1.8 KiB
Markdown
This workflow analyses Oxford Nanopore long-read RNA sequencing data. It uses
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[`bambu`](https://bioconductor.org/packages/bambu/) to build and quantify
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transcript models, can optionally run
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[`SQANTI3`](https://github.com/ConesaLab/SQANTI3) for transcript classification
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and QC, can optionally run
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[`DESeq2`](https://bioconductor.org/packages/DESeq2/) and
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[`DEXSeq`](https://bioconductor.org/packages/DEXSeq/) for differential
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analysis, and will run
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[`modkit`](https://github.com/nanoporetech/modkit) for base modification
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pileups on aligned reads if relevant tags are present.
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The workflow supports:
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+ transcript identification from either cDNA or direct RNA reads
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+ transcript discovery guided by a supplied genome and annotation
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+ quantification against a supplied reference annotation
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+ optional transcript classification and QC with `SQANTI3`
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+ differential gene expression with `DESeq2`
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+ differential transcript usage with `DEXSeq`
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+ base modification pileups with `modkit`
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The main transcriptome result is a shared `bambu` model built from all samples
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together. The workflow also produces separate per-sample transcriptomes, so
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each sample has its own GTF, FASTA, count tables, and optional `SQANTI3`
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summary alongside the shared results.
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<figure>
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<img src="docs/images/wf-transcriptomes.drawio.svg" alt="wf-transcriptomes overview schematic."/>
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<figcaption>Schematic depicting wf-transcriptomes workflow.</figcaption>
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</figure>
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For users familiar with earlier transcriptome workflows, the main change is
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that transcript discovery, quantification, and optional differential analysis
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now use the shared `bambu` outputs rather than the older
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StringTie/GffCompare/Salmon-based approach. The rest of this README explains
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the current workflow in plain terms, while the `FAQ` and `Troubleshooting`
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sections call out the main differences from the previous workflow version.
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