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Targeted DNA Methylation Analysis by Next-generation Sequencing
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Multi-genome alignment for quality control and contamination screening of next-generation sequencing data
James Hadfield1, Matthew D Eldridge2
1Genomics Core Facility, Cancer Research UK Cambridge institute, University of Cambridge Cambridge, UK.
Frontiers in Genetics
|March 7, 2014
Summary
Massive DNA sequencing data requires efficient quality control. A new multi-genome alignment tool visually assesses next-generation sequencing run quality and identifies contamination, streamlining data analysis.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- Massive DNA sequencing data presents significant challenges for biological research.
- Efficient quality control of sequencing run performance is crucial before intensive computational analysis.
Purpose of the Study:
- To develop a tool that simplifies the assessment of next-generation sequencing (NGS) run quality.
- To enable efficient human review of large-scale sequencing data.
Main Methods:
- Development of a multi-genome alignment tool.
- Presentation of NGS run data in visual and tabular formats.
- Inclusion of sample-based quality metrics and contamination screening.
Main Results:
- The tool simplifies the assessment of sequencing run yield and quality.
- It screens for adapter sequence contamination and cross-species contamination.
- Facilitates efficient quality control for large genomic datasets.
Conclusions:
- The multi-genome alignment tool enhances the efficiency of NGS data quality control.
- It supports biologists in managing and analyzing large volumes of genomic data.
- Aids in ensuring high-quality data for downstream computational processes.
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