CloudLCA: finding the lowest common ancestor in metagenome analysis using cloud computing

	CloudLCA: finding the lowest common ancestor in metagenome analysis using cloud computing
	Zhao Guoguang 1; Bu Dechao 1; Liu Changning 1; Li Jing 1; Yang Jian 3; Liu Zhiyong 1; Zhao Yi 1; Chen Runsheng 1
	2012
发表期刊	PROTEIN & CELL
ISSN	1674-800X
卷号	3 期号:2 页码:148
摘要	Estimating taxonomic content constitutes a key problem in metagenomic sequencing data analysis. However, extracting such content from high-throughput data of next-generation sequencing is very time-consuming with the currently available software. Here, we present CloudLCA, a parallel LCA algorithm that significantly improves the efficiency of determining taxonomic composition in metagenomic data analysis. Results show that CloudLCA (1) has a running time nearly linear with the increase of dataset magnitude, (2) displays linear speedup as the number of processors grows, especially for large datasets, and (3) reaches a speed of nearly 215 million reads each minute on a cluster with ten thin nodes. In comparison with MEGAN, a well-known metagenome analyzer, the speed of CloudLCA is up to 5 more times faster, and its peak memory usage is approximately 18.5% that of MEGAN, running on a fat node. CloudLCA can be run on one multiprocessor node or a cluster. It is expected to be part of MEGAN to accelerate analyzing reads, with the same output generated as MEGAN, which can be import into MEGAN in a direct way to finish the following analysis. Moreover, CloudLCA is a universal solution for finding the lowest common ancestor, and it can be applied in other fields requiring an LCA algorithm.
关键词	CloudLCA metagenome analysis cloud computing
语种	英语
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/33288
专题	中国科学院计算技术研究所期刊论文_中文
作者单位	1.中国科学院计算技术研究所 2.中国科学院大学 3.Chinese Ctr Dis Control & Prevent, Natl Institute Viral Dis Control & Prevent, State Key Lab Mol Virol & Genet Engn, Beijing 100176, Peoples R China Natl Institute Viral Dis Control & Prevent State Key Lab Mol Virol & Genet Engn 4.Chinese Acad Science, Bioinformat Lab, Beijing 100101, Peoples R China Bioinformat Lab 5.中国科学院
第一作者单位	中国科学院计算技术研究所
推荐引用方式 GB/T 7714	Zhao Guoguang,Bu Dechao,Liu Changning,et al. CloudLCA: finding the lowest common ancestor in metagenome analysis using cloud computing[J]. PROTEIN & CELL,2012,3(2):148.
APA	Zhao Guoguang.,Bu Dechao.,Liu Changning.,Li Jing.,Yang Jian.,...&Chen Runsheng.(2012).CloudLCA: finding the lowest common ancestor in metagenome analysis using cloud computing.PROTEIN & CELL,3(2),148.
MLA	Zhao Guoguang,et al."CloudLCA: finding the lowest common ancestor in metagenome analysis using cloud computing".PROTEIN & CELL 3.2(2012):148.