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Erik Arner

Publications and source records attributed to Erik Arner.

3 recordsLinked to original sources

Correcting errors in shotgun sequences.

Sequencing errors in combination with repeated regions cause major problems in shotgun sequencing, mainly due to the failure of assembly programs to distinguish single base differences between repeat copies from erroneous base calls. In this paper, a new strategy designed to correct errors in shotgun sequence data using defined nucleotide positions, DNPs, is presented. The method distinguishes single base differences from sequencing errors by analyzing multiple alignments consisting of a read and all its overlaps with other reads. The construction of multiple alignments is performed using a novel pattern matching algorithm, which takes advantage of the symmetry between indices that can be computed for similar words of the same length. This allows for rapid construction of multiple alignments, with no previous pair-wise matching of sequence reads required. Results from a C++ implementation of this method show that up to 99% of sequencing errors can be corrected, while up to 87% of the single base differences remain and up to 80% of the corrected reads contain at most one error. The results also show that the method outperforms the error correction method used in the EULER assembler. The prototype software, MisEd, is freely available from the authors for academic use.

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TRAP: Tandem Repeat Assembly Program produces improved shotgun assemblies of repetitive sequences.

The software commonly used for assembly of shotgun sequence data has several limitations. One such limitation becomes obvious when repetitive sequences are encountered. Shotgun assembly is a difficult task, even for non-repetitive regions, but the use of quality assessments of the data and efficient matching algorithms have made it possible to assemble most sequences efficiently. In the case of highly repetitive sequences, however, these algorithms fail to distinguish between sequencing errors and single base differences in regions containing nearly identical repeats. None of the currently available fragment assembly programs are able to correctly assemble highly similar repetitive data, and we, therefore, present a novel shotgun assembly program, Tandem Repeat Assembly Program (TRAP). The main feature of this program is the ability to separate long repetitive regions from each other by distinguishing single base substitutions as well as insertions/deletions from sequencing errors. This is accomplished by using a novel multiple-alignment based analysis method. Since repeats are a common complication in most sequencing projects, this software should be of use for the whole sequencing community.

Algorithms↗

Separation of nearly identical repeats in shotgun assemblies using defined nucleotide positions, DNPs.

An increasingly important problem in genome sequencing is the failure of the commonly used shotgun assembly programs to correctly assemble repetitive sequences. The assembly of non-repetitive regions or regions containing repeats considerably shorter than the average read length is in practice easy to solve, while longer repeats have been a difficult problem. We here present a statistical method to separate arbitrarily long, almost identical repeats, which makes it possible to correctly assemble complex repetitive sequence regions. The differences between repeat units may be as low as 1% and the sequencing error may be up to ten times higher. The method is based on the realization that a comparison of only a part of all overlapping sequences at a time in a data set does not generate enough information for a conclusive analysis. Our method uses optimal multi-alignments consisting of all the overlaps of each read. This makes it possible to determine defined nucleotide positions, DNPs, which constitute the differences between the repeat units. Differences between repeats are distinguished from sequencing errors using statistical methods, where the probabilities of obtaining certain combinations of candidate DNPs are calculated using the information from the multi-alignments. The use of DNPs and combinations of DNPs will allow for optimal and rapid assemblies of repeated regions. This method can solve repeats that differ in only two positions in a read length, which is the theoretical limit for repeat separation. We predict that this method will be highly useful in shotgun sequencing in the future.

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