Parallel-META 2.0: enhanced metagenomic data analysis with functional annotation, high performance computing and advanced visualization.

ABSTRACT: The metagenomic method directly sequences and analyses genome information from microbial communities. The main computational tasks for metagenomic analyses include taxonomical and functional structure analysis for all genomes in a microbial community (also referred to as a metagenomic sample). With the advancement of Next Generation Sequencing (NGS) techniques, the number of metagenomic samples and the data size for each sample are increasing rapidly. Current metagenomic analysis is both data- and computation- intensive, especially when there are many species in a metagenomic sample, and each has a large number of sequences. As such, metagenomic analyses require extensive computational power. The increasing analytical requirements further augment the challenges for computation analysis. In

SUBMITTER: Su X 

PROVIDER: S-EPMC3940597 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature