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A new efficient data structure for storage and retrieval of multiple biosequences
Sascha Steinbiss1, Stefan Kurtz
1University of Hamburg, Hamburg.
IEEE/ACM Transactions on Computational Biology and Bioinformatics
|November 16, 2011
Summary
A new data structure, GtEncseq, offers efficient storage for large biological sequences, improving genome analysis. This novel approach provides fast access and memory savings, outperforming previous methods in space and time requirements.
Area of Science:
- Bioinformatics
- Computational Biology
- Genomics
Background:
- Genome analysis demands efficient and memory-saving sequence representations for large datasets.
- Existing sequence storage solutions are often poorly reusable or language-specific, hindering broad application.
- A need exists for a generic, versatile, and efficient biological sequence data structure.
Purpose of the Study:
- To introduce GtEncseq, a novel, space-efficient data structure for storing multiple biological sequences.
- To provide a generic implementation that overcomes limitations of existing, specialized solutions.
- To offer customizable features like wildcard support and optimized internal representations.
Main Methods:
- Development of a C-implemented, portable software library for biological sequence storage.
- Incorporation of features such as variable alphabet size, character transformations, and wildcard support.
- Optimization of internal representations based on wildcard distribution and sequence length.
Main Results:
- GtEncseq achieves remarkable space efficiency, requiring only 2 + 8 × 10^-6 bits per character for the human genome.
- The implementation supports random and sequential access, including different reading directions, via an object-oriented interface.
- Benchmarks demonstrate competitive space and time performance compared to existing solutions.
Conclusions:
- GtEncseq offers a versatile and efficient solution for biological sequence representation in large-scale genome analysis.
- Its features and performance make it a valuable tool for bioinformatics and computational biology applications.
- The library's extensibility allows integration with various scripting languages, enhancing its utility.
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