Rapid parallel genome indexing with MapReduce
Proceedings of the second international workshop on MapReduce and its applications
PSAEC: an improved algorithm for short read error correction using partial suffix arrays
FAW-AAIM'11 Proceedings of the 5th joint international frontiers in algorithmics, and 7th international conference on Algorithmic aspects in information and management
An efficient hybrid approach to correcting errors in short reads
MDAI'11 Proceedings of the 8th international conference on Modeling decisions for artificial intelligence
Suffix-Tree Based Error Correction of NGS Reads Using Multiple Manifestations of an Error
Proceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical Informatics
Computational Biology and Chemistry
Hi-index | 3.84 |
Motivation: High-throughput sequencing technologies produce very large amounts of data and sequencing errors constitute one of the major problems in analyzing such data. Current algorithms for correcting these errors are not very accurate and do not automatically adapt to the given data. Results: We present HiTEC, an algorithm that provides a highly accurate, robust and fully automated method to correct reads produced by high-throughput sequencing methods. Our approach provides significantly higher accuracy than previous methods. It is time and space efficient and works very well for all read lengths, genome sizes and coverage levels. Availability: The source code of HiTEC is freely available at www.csd.uwo.ca/~ilie/HiTEC/. Contact: ilie@csd.uwo.ca