Bioinformatics
Bioinformatics is part of the Nanopore Wiki learning path. Nanopore bioinformatics converts raw signals and reads into interpretable sequence, alignment, assembly, variant, modification, and classification results.
Core concepts
- Basecalling converts raw signal into sequence and quality values.
- Read quality, length distribution, adapters, contamination, and coverage shape downstream results.
- Long reads support assembly and structural variant discovery but still require quality-aware analysis.
- Model and software versions are part of the scientific record.
Scientific basis
- Basecalling converts raw signal into sequence and quality values.
- Read quality, length distribution, adapters, contamination, and coverage shape downstream results.
- Interpretations should be tied to measurable quantities, experimental controls, and documented analysis settings.
- Claims should distinguish direct observations from downstream inference.
Sequencing data workflow
| Step | Description |
|---|---|
| 1 | Collect raw signal and run metadata. |
| 2 | Basecall into reads and quality scores. |
| 3 | Run quality control and filtering. |
| 4 | Align, assemble, classify, call variants, or detect modifications according to the question. |
| 5 | Report tools, versions, parameters, and reference data. |
Typical applications
- Genome assembly.
- Structural variant detection.
- Metagenomics and pathogen classification.
- RNA sequencing and modification detection.
Quality checks
- Record platform, pore or flow-cell type, chemistry, voltage or acquisition settings, and software versions.
- Use negative controls, positive controls, and replicate measurements where the claim depends on specificity.
- Report limitations such as noise, bias, sample degradation, pore instability, or model-dependent analysis.
- Keep laboratory metadata linked to the raw signal or sequencing run before interpreting results.
Interpretation limits
- Using a pipeline without recording model versions.
- Ignoring contamination and coverage bias.
- A single result should not be generalized beyond the sample, protocol, instrument state, and analysis pipeline used.
- Medical, legal, regulatory, or commercial decisions require domain-specific validation beyond this educational summary.