MOTIVATION: Next-generation sequence analysis has become an important task both in laboratory and clinical settings. A key stage in the majority sequence analysis workflows, such as resequencing, is the alignment of genomic reads to a reference genome. The accurate alignment of reads with large indels is a computationally challenging task for researchers. RESULTS: We introduce SeqAlto as a new algorithm for read alignment. For reads longer than or equal to 100 bp, SeqAlto is up to 10 × faster than existing algorithms, while retaining high accuracy and the ability to align reads with large (up to 50 bp) indels. This improvement in efficiency is particularly important in the analysis of future sequencing data where the number of reads approaches many billions. Furthermore, SeqAlto uses less than 8 GB of memory to align against the human genome. SeqAlto is benchmarked against several existing tools with both real and simulated data. AVAILABILITY: Linux and Mac OS X binaries free for academic use are available at http://www.stanford.edu/group/wonglab/seqalto CONTACT: whwong@stanford.edu.
MOTIVATION: Next-generation sequence analysis has become an important task both in laboratory and clinical settings. A key stage in the majority sequence analysis workflows, such as resequencing, is the alignment of genomic reads to a reference genome. The accurate alignment of reads with large indels is a computationally challenging task for researchers. RESULTS: We introduce SeqAlto as a new algorithm for read alignment. For reads longer than or equal to 100 bp, SeqAlto is up to 10 × faster than existing algorithms, while retaining high accuracy and the ability to align reads with large (up to 50 bp) indels. This improvement in efficiency is particularly important in the analysis of future sequencing data where the number of reads approaches many billions. Furthermore, SeqAlto uses less than 8 GB of memory to align against the human genome. SeqAlto is benchmarked against several existing tools with both real and simulated data. AVAILABILITY: Linux and Mac OS X binaries free for academic use are available at http://www.stanford.edu/group/wonglab/seqalto CONTACT: whwong@stanford.edu.
Authors: Gonçalo R Abecasis; David Altshuler; Adam Auton; Lisa D Brooks; Richard M Durbin; Richard A Gibbs; Matt E Hurles; Gil A McVean Journal: Nature Date: 2010-10-28 Impact factor: 49.962
Authors: Shu-Hong Gao; Jun Yuan Ho; Lu Fan; David J Richardson; Zhiguo Yuan; Philip L Bond Journal: Appl Environ Microbiol Date: 2016-08-30 Impact factor: 4.792