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A comparative evaluation of genome assembly reconciliation tools.
Hind Alhakami1, Hamid Mirebrahim2, Stefano Lonardi2
1Department of Computer Science & Engineering, University of California, 900 University Avenue, Riverside, 92521, CA, USA. halha004@cs.ucr.edu.
Genome Biology
|May 20, 2017
Summary
Assembly reconciliation tools aim to merge genome assemblies for improved quality. However, this study found no single tool consistently enhanced assembly quality, with results varying based on input data and specific algorithms used.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- Eukaryotic genome assembly is challenging, often resulting in incomplete sequences.
- Multiple assembly tools and parameters exist, making tool selection difficult.
- Assembly reconciliation offers a promising approach to improve genome assembly quality by merging existing assemblies.
Purpose of the Study:
- To conduct a comprehensive comparative evaluation of existing assembly reconciliation tools.
- To assess the strengths and weaknesses of these tools on a common dataset.
- To provide insights into selecting appropriate tools for genome assembly reconciliation.
Main Methods:
- Evaluation of several assembly reconciliation tools using GAGE and synthetic datasets.
- Assessment metrics included contiguity, correctness, coverage, and duplication ratio.
- Comparison of merged assembly quality against individual input assemblies.
Main Results:
- No tested tool consistently improved the quality of all input assemblies.
- Increased contiguity was observed when input assemblies were already of high quality.
- Correctness of the merged assembly varied, depending on the tool and input assembly quality.
Conclusions:
- Assembly reconciliation tools do not guarantee improved genome assembly quality.
- The effectiveness of reconciliation tools is highly dependent on the quality of the input assemblies.
- Careful selection of tools and consideration of input data are crucial for successful genome assembly reconciliation.
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