MEGAN analysis of metagenomic data
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TLDR
MEGAN, a new computer program that allows laptop analysis of large metagenomic data sets, is introduced and provides graphical and statistical output for comparing different data sets.Abstract:
Metagenomics is the study of the genomic content of a sample of organisms obtained from a common habitat using targeted or random sequencing. Goals include understanding the extent and role of microbial diversity. The taxonomical content of such a sample is usually estimated by comparison against sequence databases of known sequences. Most published studies use the analysis of paired-end reads, complete sequences of environmental fosmid and BAC clones, or environmental assemblies. Emerging sequencing-by-synthesis technologies with very high throughput are paving the way to low-cost random “shotgun” approaches. This paper introduces MEGAN, a new computer program that allows laptop analysis of large metagenomic data sets. In a preprocessing step, the set of DNA sequences is compared against databases of known sequences using BLAST or another comparison tool. MEGAN is then used to compute and explore the taxonomical content of the data set, employing the NCBI taxonomy to summarize and order the results. A simple lowest common ancestor algorithm assigns reads to taxa such that the taxonomical level of the assigned taxon reflects the level of conservation of the sequence. The software allows large data sets to be dissected without the need for assembly or the targeting of specific phylogenetic markers. It provides graphical and statistical output for comparing different data sets. The approach is applied to several data sets, including the Sargasso Sea data set, a recently published metagenomic data set sampled from a mammoth bone, and several complete microbial genomes. Also, simulations that evaluate the performance of the approach for different read lengths are presented.read more
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Journal ArticleDOI
A human gut microbial gene catalogue established by metagenomic sequencing
Junjie Qin,Ruiqiang Li,Jeroen Raes,Manimozhiyan Arumugam,Kristoffer Sølvsten Burgdorf,Chaysavanh Manichanh,Trine Nielsen,Nicolas Pons,Florence Levenez,Takuji Yamada,Daniel R. Mende,Junhua Li,Junming Xu,Shaochuan Li,Dongfang Li,Jianjun Cao,Bo Wang,Huiqing Liang,Huisong Zheng,Yinlong Xie,Julien Tap,Patricia Lepage,Marcelo Bertalan,Jean-Michel Batto,Torben Hansen,Denis Le Paslier,Allan Linneberg,H. Bjørn Nielsen,Eric Pelletier,Pierre Renault,Thomas Sicheritz-Pontén,Keith Turner,Hongmei Zhu,Chang Yu,Shengting Li,Min Jian,Yan Zhou,Yingrui Li,Xiuqing Zhang,Songgang Li,Nan Qin,Huanming Yang,Jian Wang,Søren Brunak,Joël Doré,Francisco Guarner,Karsten Kristiansen,Oluf Pedersen,Julian Parkhill,Jean Weissenbach,Peer Bork,S. Dusko Ehrlich,Jun Wang +52 more
TL;DR: The Illumina-based metagenomic sequencing, assembly and characterization of 3.3 million non-redundant microbial genes, derived from 576.7 gigabases of sequence, from faecal samples of 124 European individuals are described, indicating that the entire cohort harbours between 1,000 and 1,150 prevalent bacterial species and each individual at least 160 such species.
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Diet-induced obesity is linked to marked but reversible alterations in the mouse distal gut microbiome
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Succession of microbial consortia in the developing infant gut microbiome
Jeremy E. Koenig,Aymé Spor,Nicholas B. Scalfone,Ashwana D. Fricker,Jesse Stombaugh,Rob Knight,Largus T. Angenent,Ruth E. Ley +7 more
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