Kalign2: high-performance multiple alignment of protein and nucleotide sequences allowing external features. In the growing field of genomics, multiple alignment programs are confronted with ever increasing amounts of data. To address this growing issue we have dramatically improved the running time and memory requirement of Kalign, while maintaining its high alignment accuracy. Kalign version 2 also supports nucleotide alignment, and a newly introduced extension allows for external sequence annotation to be included into the alignment procedure. We demonstrate that Kalign2 is exceptionally fast and memory-efficient, permitting accurate alignment of very large numbers of sequences. The accuracy of Kalign2 compares well to the best methods in the case of protein alignments while its accuracy on nucleotide alignments is generally superior. In addition, we demonstrate the potential of using known or predicted sequence annotation to improve the alignment accuracy. Kalign2 is freely available for download from the Kalign web site (http://msa.sbc.su.se/).

References in zbMATH (referenced in 13 articles )

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  1. Alves Moreira, Carlos; Philot, Eric Allison; Lima, Angélica Nakagawa; Scott, Ana Ligia: Predicting regions prone to protein aggregation based on SVM algorithm (2019)
  2. DeBlasio, Dan; Kececioglu, John: Parameter advising for multiple sequence alignment (2017)
  3. Keith, Jonathan M. (ed.): Bioinformatics. Volume I. Data, sequence analysis, and evolution (2017)
  4. Nguyen, Ken; Guo, Xuan; Pan, Yi: Multiple biological sequence alignment. Scoring functions, algorithms and evaluation (2016)
  5. Federico, Maria; Peterlongo, Pierre; Pisanti, Nadia; Sagot, Marie-France: \textscRime: repeat identification (2014)
  6. Heaps, Sarah E.; Nye, Tom M. W.; Boys, Richard J.; Williams, Tom A.; Embley, T. Martin: Bayesian modelling of compositional heterogeneity in molecular phylogenetics (2014)
  7. Daugelaite, Jurate; O’Driscoll, Aisling; Sleator, Roy D.: An overview of multiple sequence alignments and cloud computing in bioinformatics (2013)
  8. Gudyś, Adam; Deorowicz, Sebastian: A parallel algorithm for the constrained multiple sequence alignment problem designed for GPUs (2012)
  9. Petitjean, François; Gançarski, Pierre: Summarizing a set of time series by averaging: from Steiner sequence to compact multiple alignment (2012)
  10. Petitjean, François; Ketterlin, Alain; Gançarski, Pierre: A global averaging method for dynamic time warping, with applications to clustering (2011)
  11. Edgar, Robert C.: Optimizing substitution matrix choice and gap parameters for sequence alignment (2009) ioport
  12. Spjuth, Ola; Alvarsson, Jonathan; Berg, Arvid; Eklund, Martin; Kuhn, Stefan; Mäsak, Carl; Torrance, Gilleain M.; Wagener, Johannes; Willighagen, Egon L.; Steinbeck, Christoph; Wikberg, Jarl E. S.: Bioclipse 2: A scriptable integration platform for the life sciences (2009) ioport
  13. Lassmann, Timo; Sonnhammer, Erik L. L.: Kalign, kalignvu and mumsa: Web servers for multiple sequence alignment. (2006) ioport