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BOSS: a novel scaffolding algorithm based on an optimized scaffold graph.

Junwei Luo^1,2, Jianxin Wang¹, Zhen Zhang¹

¹School of Information Science and Engineering, Central South University, ChangSha 410083, China.

Bioinformatics (Oxford, England)

|September 17, 2016

Summary

This summary is machine-generated.

BOSS is a novel algorithm for genome assembly scaffolding. It uses paired reads and an iterative strategy to build accurate scaffold graphs, improving contig ordering and completeness compared to existing tools.

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Area of Science:

Bioinformatics
Genomics
Computational Biology

Background:

Scaffolding is crucial for genome assembly, aiming to order and orient fragmented contigs.
Existing scaffold graph methods face challenges due to repetitive regions, sequencing errors, and depth variations.

Purpose of the Study:

To present a novel scaffolding algorithm, BOSS (Bionformatics Open Source Scaffolder).
To improve the accuracy and completeness of genome assembly scaffolding.

Main Methods:

BOSS employs paired reads and insert size distribution to construct and weigh scaffold graphs.
An iterative strategy is used to detect and remove spurious edges, ensuring graph consistency.
A heuristic algorithm sorts contigs based on the scaffold graph to generate final scaffolds.

Main Results:

BOSS demonstrates superior performance in producing more satisfactory scaffolds compared to other popular tools.
Experiments on real sequencing data from four genomes validate BOSS's effectiveness.
The algorithm successfully addresses challenges in constructing accurate scaffold graphs.

Conclusions:

BOSS offers a robust and effective approach to genome assembly scaffolding.
The algorithm's iterative edge removal strategy enhances scaffold graph accuracy.
BOSS provides a valuable tool for improving genome assembly results.