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BrownieAligner: accurate alignment of Illumina sequencing data to de Bruijn graphs.

Mahdi HeydariGiles MiclotteYves Van de PeerJan Fostier
Published in: BMC bioinformatics (2018)
BrownieAligner is applied to both synthetic and real datasets. It generally outperforms other state-of-the-art tools in terms of accuracy, while having similar runtime and memory requirements. Our results show that using the higher-order Markov model in BrownieAligner improves the accuracy, while the branch and bound algorithm reduces runtime. BrownieAligner is written in standard C++11 and released under GPL license. BrownieAligner relies on multithreading to take advantage of multi-core/multi-CPU systems. The source code is available at: https://github.com/biointec/browniealigner.
Keyphrases
  • machine learning
  • single cell
  • electronic health record
  • working memory
  • rna seq
  • big data
  • artificial intelligence