Suffix tree searcher: exploration of common substrings in large DNA sequence sets

BMC Research Notes

Chris Upton¹  Chris Kelly¹  Marina G Barsky²  Song-Han Lin¹  Michael J Whitney¹  David Minkley¹ 

[1] Department of Biochemistry and Microbiology, University of Victoria, Ring Road, Victoria, BC V8W 3P6, Canada;Current address: Ontario Institute for Cancer Research, MaRS Centre, Toronto, ON M5G 0A3, Canada

关键词: STS;    DNA sequence;    Substring;    Genome;    Suffix tree;   

Others  :  1131833
DOI  :  10.1186/1756-0500-7-466

 received in 2014-02-12, accepted in 2014-07-18,  发布年份 2014

【 摘 要 】

Background

Large DNA sequence data sets require special bioinformatics tools to search and compare them. Such tools should be easy to use so that the data can be easily accessed by a wide array of researchers. In the past, the use of suffix trees for searching DNA sequences has been limited by a practical need to keep the trees in RAM. Newer algorithms solve this problem by using disk-based approaches. However, none of the fastest suffix tree algorithms have been implemented with a graphical user interface, preventing their incorporation into a feasible laboratory workflow.

Results

Suffix Tree Searcher (STS) is designed as an easy-to-use tool to index, search, and analyze very large DNA sequence datasets. The program accommodates very large numbers of very large sequences, with aggregate size reaching tens of billions of nucleotides. The program makes use of pre-sorted persistent "building blocks" to reduce the time required to construct new trees. STS is comprised of a graphical user interface written in Java, and four C modules. All components are automatically downloaded when a web link is clicked. The underlying suffix tree data structure permits extremely fast searching for specific nucleotide strings, with wild cards or mismatches allowed. Complete tree traversals for detecting common substrings are also very fast. The graphical user interface allows the user to transition seamlessly between building, traversing, and searching the dataset.

Conclusions

Thus, STS provides a new resource for the detection of substrings common to multiple DNA sequences or within a single sequence, for truly huge data sets. The re-searching of sequence hits, allowing wild card positions or mismatched nucleotides, together with the ability to rapidly retrieve large numbers of sequence hits from the DNA sequence files, provides the user with an efficient method of evaluating the similarity between nucleotide sequences by multiple alignment or use of Logos. The ability to re-use existing suffix tree pieces considerably shortens index generation time. The graphical user interface enables quick mastery of the analysis functions, easy access to the generated data, and seamless workflow integration.

【 授权许可】

   
2014 Minkley et al.; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

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