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MinIONQC: fast and simple quality control for MinION sequencing data
R Lanfear1, M Schalamun1, D Kainer1
1The Research School of Biology, Australian National University, Canberra ACT 2601, Australia.
Bioinformatics (Oxford, England)
|July 28, 2018
Summary
MinIONQC offers rapid quality control and diagnostic plots for Oxford Nanopore MinION sequencing data. This tool aids in optimizing protocols and comparing multiple flowcells for publication-ready results.
Area of Science:
- Bioinformatics
- Genomics
- Molecular Biology
Background:
- Oxford Nanopore Technologies' MinION platform generates significant sequencing data.
- Effective quality control is crucial for reliable genomic analysis.
- Optimizing library preparation and sequencing protocols requires timely feedback.
Purpose of the Study:
- To introduce MinIONQC, a software tool for rapid quality assessment of MinION sequencing data.
- To provide diagnostic plots for evaluating sequencing performance.
- To facilitate comparison of data across multiple flowcells.
Main Methods:
- MinIONQC is implemented in the R programming language.
- The tool processes sequencing data from MinION flowcells.
- It generates various quality control metrics and visualizations.
Main Results:
- Provides rapid, diagnostic plots for MinION sequencing data.
- Enables direct comparison of data quality across multiple flowcells.
- Generates publication-ready figures summarizing sequencing data.
Conclusions:
- MinIONQC assists in optimizing DNA extraction, library preparation, and sequencing protocols.
- The software facilitates efficient quality control for MinION users.
- It supports reliable genomic data analysis by ensuring data quality.
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