Bioinformatics: Difference between revisions
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[[File:Nanopore_DNA_sequencing.png|thumb|right|320px| | [[File:Nanopore_DNA_sequencing.png|thumb|right|320px|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. | '''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. | ||
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== 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. | |||
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== Sequencing data workflow == | == Sequencing data workflow == | ||
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== Typical applications == | == Typical applications == | ||
* Genome assembly. | * Genome assembly. | ||
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* RNA sequencing and modification detection. | * RNA sequencing and modification detection. | ||
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== | == 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. | |||
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== Interpretation limits == | |||
* Using a pipeline without recording model versions. | * Using a pipeline without recording model versions. | ||
* Ignoring contamination and coverage bias. | * 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. | |||
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== Related pages == | == Related pages == | ||
* [[Nanopore sequencing]] | * [[Nanopore sequencing]] | ||
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* [[Glossary]] | * [[Glossary]] | ||
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== References == | == References == | ||
* [https://en.wikipedia.org/wiki/Bioinformatics Bioinformatics] | * [https://en.wikipedia.org/wiki/Bioinformatics Bioinformatics] | ||
Latest revision as of 09:25, 15 July 2026
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.