Journal
BRIEFINGS IN BIOINFORMATICS
Volume 14, Issue 1, Pages 56-66Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bib/bbs015
Keywords
error correction; next-generation sequencing; sequence analysis
Funding
- US National Science Foundation [DMS-1120597]
- Department of Science and Technology Swarnajayanti Fellowship from the Government of India
- Division Of Mathematical Sciences
- Direct For Mathematical & Physical Scien [1120597] Funding Source: National Science Foundation
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Error Correction is important for most next-generation sequencing applications because highly accurate sequenced reads will likely lead to higher quality results. Many techniques for error correction of sequencing data from next-gen platforms have been developed in the recent years. However, compared with the fast development of sequencing technologies, there is a lack of standardized evaluation procedure for different error-correction methods, making it difficult to assess their relative merits and demerits. In this article, we provide a comprehensive review of many error-correction methods, and establish a common set of benchmark data and evaluation criteria to provide a comparative assessment. We present experimental results on quality, run-time, memory usage and scalability of several error-correction methods. Apart from providing explicit recommendations useful to practitioners, the review serves to identify the current state of the art and promising directions for future research. Availability: All error-correction programs used in this article are downloaded from hosting websites. The evaluation tool kit is publicly available at: http://aluru-sun.ece.iastate.edu/doku.php?id=ecr.
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