Bioinformatics

Nanopore bioinformatics converts raw signal into interpretable sequence evidence.

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.

Related pages

• Nanopore sequencing
• Data analysis
• Event detection
• Glossary

References

• Bioinformatics
• Sequence alignment