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3' End Sequencing Library Preparation with A-seq2
Published on: October 10, 2017
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Investigation into the annotation of protocol sequencing steps in the sequence read archive
Jamie Alnasir1, Hugh P Shanahan1
1Department of Computer Science, Royal Holloway, University of London, Egham, TW20 0EX UK.
Gigascience
|May 12, 2015
Summary
High-throughput sequencing data preparation lacks detailed annotation in the Sequence Read Archive (SRA). This limits the ability to systematically study and quantify bias introduced during critical library preparation steps.
Area of Science:
- Genomics
- Bioinformatics
- Molecular Biology
Background:
- High-throughput sequencing data generation involves a complex workflow with multiple protocol steps.
- Key library preparation stages, including DNA fractionation, blunting, phosphorylation, adapter ligation, and library enrichment, require accurate quantification of associated bias.
- The extent of bias introduced by these specific protocol steps remains largely undetermined.
Purpose of the Study:
- To assess the level of annotation for critical sequencing protocol steps within the Sequence Read Archive (SRA) database.
- To determine if experimental metadata adequately describes key library preparation stages for downstream analysis.
Main Methods:
- Utilized SQL relational database queries on the SRAdb SQLite database.
- Searched for keywords associated with DNA fragmentation, adapter ligation, and library enrichment across SRA records.
- Analyzed metadata from studies submitted to the Sequence Read Archive.
Main Results:
- Only 7.10% (fragmentation), 5.84% (ligation), and 7.57% (enrichment) of SRA records contained keywords for at least one of these three protocol steps.
- A mere 4.06% of all SRA records included keywords for all three critical library preparation steps.
- This indicates a low level of detailed annotation for essential sequencing workflow components.
Conclusions:
- The current annotation level in the SRA database hinders systematic investigations into protocol-specific biases.
- Lack of detailed metadata prevents the quantification of bias in high-throughput sequencing data.
- Future meta-analyses and comparative studies using SRA data are susceptible to unquantified sources of bias.
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