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Grinder: a versatile amplicon and shotgun sequence simulator
被引:134
作者:
Angly, Florent E.
[1
]
Willner, Dana
[1
,2
]
Rohwer, Forest
[3
]
Hugenholtz, Philip
[1
,4
]
Tyson, Gene W.
[1
,5
]
机构:
[1] Australian Ctr Ecogen, Sch Chem & Mol Biosci, Sydney, NSW, Australia
[2] Univ Queensland, Diamantina Inst, St Lucia, Qld 4072, Australia
[3] San Diego State Univ, Dept Biol, San Diego, CA 92182 USA
[4] Univ Queensland, Inst Mol Biosci, St Lucia, Qld 4072, Australia
[5] Univ Queensland, Adv Water Management Ctr, St Lucia, Qld 4072, Australia
基金:
澳大利亚研究理事会;
关键词:
454 PYROSEQUENCING DATA;
RIBOSOMAL-RNA GENE;
HIGH-THROUGHPUT;
MICROBIAL DIVERSITY;
RARE BIOSPHERE;
DATA SETS;
DATABASE;
BIAS;
METAGENOMICS;
GENOMES;
D O I:
10.1093/nar/gks251
中图分类号:
Q5 [生物化学];
Q7 [分子生物学];
学科分类号:
071010 ;
081704 ;
摘要:
We introduce Grinder (http://sourceforge.net/projects/biogrinder/), an open-source bioinformatic tool to simulate amplicon and shotgun (genomic, metagenomic, transcriptomic and metatranscriptomic) datasets from reference sequences. This is the first tool to simulate amplicon datasets (e.g. 16S rRNA) widely used by microbial ecologists. Grinder can create sequence libraries with a specific community structure, alpha and beta diversities and experimental biases (e.g. chimeras, gene copy number variation) for commonly used sequencing platforms. This versatility allows the creation of simple to complex read datasets necessary for hypothesis testing when developing bioinformatic software, benchmarking existing tools or designing sequence-based experiments. Grinder is particularly useful for simulating clinical or environmental microbial communities and complements the use of in vitro mock communities.
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