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Error correction of high-throughput sequencing datasets with non-uniform coverage
Author(s) -
Paul Medvedev,
Eric Scott,
Boyko Kakaradov,
Pavel A. Pevzner
Publication year - 2011
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btr208
Subject(s) - computer science , error detection and correction , throughput , simple (philosophy) , hamming graph , algorithm , hamming distance , hamming code , data mining , decoding methods , telecommunications , philosophy , epistemology , wireless , block code
The continuing improvements to high-throughput sequencing (HTS) platforms have begun to unfold a myriad of new applications. As a result, error correction of sequencing reads remains an important problem. Though several tools do an excellent job of correcting datasets where the reads are sampled close to uniformly, the problem of correcting reads coming from drastically non-uniform datasets, such as those from single-cell sequencing, remains open.

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