NDLI: ResSeq: enhancing short-read sequencing alignment by rescuing error-containing reads

Content Provider	ACM Digital Library
Author	Feng, Weixing Dong, Yansheng Liu, Yunlong Li, Meng Cao, Fenglin Sang, Peichao Lian, Deyuan Song, Fengfei He, Bo
Copyright Year	2015
Description	Author Affiliation: Harbin Engineering University, Harbin, China(Liu, Yunlong; Cao, Fenglin; He, Bo; Li, Meng; Song, Fengfei; Dong, Yansheng; Lian, Deyuan; Sang, Peichao; Feng, Weixing)
Abstract	Next-generation short-read sequencing is widely utilized in genomic studies. Biological applications require an alignment step to map sequencing reads to the reference genome, before acquiring expected genomic information. This requirement makes alignment accuracy a key factor for effective biological interpretation. Normally, when accounting for measurement errors and single nucleotide polymorphisms, short read mappings with a few mismatches are generally considered acceptable. However, to further improve the efficiency of short-read sequencing alignment, we propose a method to retrieve additional reliably aligned reads (reads with more than a pre-defined number of mismatches), using a Bayesian-based approach. In this method, we first retrieve the sequence context around the mismatched nucleotides within the already aligned reads; these loci contain the genomic features where sequencing errors occur. Then, using the derived pattern, we evaluate the remaining (typically discarded) reads with more than the allowed number of mismatches, and calculate a score that represents the probability that a specific alignment is correct. This strategy allows the extraction of more reliably aligned reads, therefore improving alignment sensitivity. Implementation: The source code of our tool, ResSeq, can be downloaded from: https://github.com/hrbeubiocenter/Resseq.
Starting Page	795
Ending Page	798
Page Count	4
File Format	PDF
ISSN	15455963
DOI	10.1109/TCBB.2014.2366103
Volume Number	12
Issue Number	4
Journal	IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-07-01
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Alignment Error analysis Sequencing Short-read
Content Type	Text
Resource Type	Article
Subject	Genetics Biotechnology Applied Mathematics

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