Dataset Information

Pluribus-Exploring the Limits of Error Correction Using a Suffix Tree.

ABSTRACT: Next generation sequencing technologies enable efficient and cost-effective genome sequencing. However, sequencing errors increase the complexity of the de novo assembly process, and reduce the quality of the assembled sequences. Many error correction techniques utilizing substring frequencies have been developed to mitigate this effect. In this paper, we present a novel and effective method called Pluribus, for correcting sequencing errors using a generalized suffix trie. Pluribus utilizes multiple manifestations of an error in the trie to accurately identify errors and suggest corrections. We show that Pluribus produces the least number of false positives across a diverse set of real sequencing datasets when compared to other methods. Furthermore, Pluribus can be used in conjunction with other contemporary error correction methods to achieve higher levels of accuracy than either tool alone. These increases in error correction accuracy are also realized in the quality of the contigs that are generated during assembly. We explore, in-depth, the behavior of Pluribus , to explain the observed improvement in accuracy and assembly performance. Pluribus is freely available at http://compbio. CASE:edu/pluribus/.

SUBMITTER: Savel D

PROVIDER: S-EPMC5754272 | biostudies-literature | 2017 Nov-Dec

REPOSITORIES: biostudies-literature

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Pluribus-Exploring the Limits of Error Correction Using a Suffix Tree.

Savel Daniel D LaFramboise Thomas T Grama Ananth A Koyuturk Mehmet M

IEEE/ACM transactions on computational biology and bioinformatics 20160629 6

Next generation sequencing technologies enable efficient and cost-effective genome sequencing. However, sequencing errors increase the complexity of the de novo assembly process, and reduce the quality of the assembled sequences. Many error correction techniques utilizing substring frequencies have been developed to mitigate this effect. In this paper, we present a novel and effective method called Pluribus, for correcting sequencing errors using a generalized suffix trie. Pluribus utilizes mult ...[more]

PMID: 27362987

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Project description: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.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.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.

Dataset Information

Pluribus-Exploring the Limits of Error Correction Using a Suffix Tree.

Publications

Pluribus-Exploring the Limits of Error Correction Using a Suffix Tree.

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