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LightAssembler: fast and memory-efficient assembly algorithm for high-throughput sequencing reads
Author(s) -
Sara ElMetwally,
Magdi Zakaria,
Taher Hamza
Publication year - 2016
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btw470
Subject(s) - computer science , sequence assembly , de bruijn graph , algorithm , parallel computing , benchmark (surveying) , graph traversal , graph , workflow , data structure , bloom filter , throughput , tree traversal , theoretical computer science , programming language , database , operating system , biology , biochemistry , gene expression , transcriptome , geodesy , gene , geography , wireless
The deluge of current sequenced data has exceeded Moore's Law, more than doubling every 2 years since the next-generation sequencing (NGS) technologies were invented. Accordingly, we will able to generate more and more data with high speed at fixed cost, but lack the computational resources to store, process and analyze it. With error prone high throughput NGS reads and genomic repeats, the assembly graph contains massive amount of redundant nodes and branching edges. Most assembly pipelines require this large graph to reside in memory to start their workflows, which is intractable for mammalian genomes. Resource-efficient genome assemblers combine both the power of advanced computing techniques and innovative data structures to encode the assembly graph efficiently in a computer memory.

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