title: EPGA2: memory-efficient de novo assembler.
abstract: BACKGROUND
  In genome assembly, as coverage of sequencing and genome size growing, most current softwares require a large memory for handling a great deal of sequence data. However, most researchers usually cannot meet the requirements of computing resources which prevent most current softwares from practical applications.
  
  
  RESULTS
  In this article, we present an update algorithm called EPGA2, which applies some new modules and can bring about improved assembly results in small memory. For reducing peak memory in genome assembly, EPGA2 adopts memory-efficient DSK to count K-mers and revised BCALM to construct De Bruijn Graph. Moreover, EPGA2 parallels the step of Contigs Merging and adds Errors Correction in its pipeline. Our experiments demonstrate that all these changes in EPGA2 are more useful for genome assembly.
  
  
  METHODS
  EPGA2 is publicly available for download at https://github.com/bioinfomaticsCSU/EPGA2.
authors: School of Information Science and Engineering, Central South University, ChangSha, 410083, China, College of Computer Science and Technology, Henan Polytechnic University, JiaoZuo, 454000, China.
authors: Junwei
authors: J
authors: Luo
authors: School of Information Science and Engineering, Central South University, ChangSha, 410083, China.
authors: Jianxin
authors: J
authors: Wang
authors: School of Information Science and Engineering, Central South University, ChangSha, 410083, China.
authors: Weilong
authors: W
authors: Li
authors: School of Information Science and Engineering, Central South University, ChangSha, 410083, China.
authors: Zhen
authors: Z
authors: Zhang
authors: Division of Biomedical Engineering, University of Saskatchewan, Saskatchewan, S7N 5A9, Canada and.
authors: Fang-Xiang
authors: FX
authors: Wu
authors: School of Information Science and Engineering, Central South University, ChangSha, 410083, China.
authors: Min
authors: M
authors: Li
authors: Department of Computer Science, Georgia State University, Atlanta, GA 30302, USA.
authors: Yi
authors: Y
authors: Pan
mesh_terms: D000465:Algorithms; D023281:Genomics / Q000379:methods*; D017422:Sequence Analysis, DNA; D012984:Software