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Boquila: NGS read simulator to eliminate read nucleotide bias in sequence analysis
Ümit Akköse1, Ogün Adebali1,2
1Faculty of Engineering and Natural Sciences, Sabancı University, İstanbul, Turkey.
Turkish Journal of Biology = Turk Biyoloji Dergisi
|August 2, 2023
Summary
Next-generation sequencing (NGS) reads can be biased by genome nucleotide content. Boquila generates mimicking sequences to correct this bias, improving genome-wide data accuracy for various applications.
Area of Science:
- Genomics
- Bioinformatics
- Molecular Biology
Background:
- Genome-wide nucleotide content is inherently heterogeneous.
- Next-generation sequencing (NGS) reads exhibit biases influenced by this nucleotide distribution.
- Such biases can affect the accuracy of genome-wide analyses.
Purpose of the Study:
- To introduce Boquila, a novel tool for correcting nucleotide-based biases in NGS data.
- To enhance the accuracy of genome-wide sequencing read distribution.
- To provide a flexible solution for bias correction in various genomic applications.
Main Methods:
- Boquila generates synthetic sequences that replicate the nucleotide profile of true NGS reads.
- The tool can be configured to focus on specific genomic regions.
- It incorporates input DNA sequencing data to correct for copy number variations.
Main Results:
- Boquila effectively mimics the nucleotide profile of actual sequencing reads.
- The tool successfully corrects for nucleotide-based biases in genome-wide NGS data.
- It offers flexibility in targeting specific regions and incorporating copy number variation data.
Conclusions:
- Boquila provides a robust method for mitigating nucleotide bias in NGS data.
- The tool enhances the reliability of genome-wide sequencing studies.
- Its compatibility with standard formats facilitates integration into existing bioinformatics workflows.
