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CloudLCA: finding the lowest common ancestor in metagenome analysis using cloud computing |
Guoguang Zhao1,4, Dechao Bu1,4, Changning Liu1, Jing Li1, Jian Yang3, Zhiyong Liu1, Yi Zhao1( ), Runsheng Chen1,2() |
| 1. Bioinformatics Research Group, Key Laboratory of Intelligent Information Processing, Advanced Computing Research Laboratory, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China; 2. Bioinformatics Laboratory and National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China; 3. State Key Laboratory for Molecular Virology and Genetic Engineering, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100176, China; 4. Graduate School of the Chinese Academy of Sciences, Beijing 100190, China |
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Abstract 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.
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| Keywords
CloudLCA
metagenome analysis
cloud computing
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Corresponding Author(s):
Zhao Yi,Email:biozy@ict.ac.cn; Chen Runsheng,Email:chenrs@sun5.ibp.ac.cn
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Issue Date: 01 February 2012
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