4.8 Article

Ribosomal Database Project: data and tools for high throughput rRNA analysis

期刊

NUCLEIC ACIDS RESEARCH
卷 42, 期 D1, 页码 D633-D642

出版社

OXFORD UNIV PRESS
DOI: 10.1093/nar/gkt1244

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资金

  1. Office of Science (Biological and Environmental Research), US Department of Energy [DE-FG02-99ER62848, DE-SC0004601]
  2. Bioenergy Center [DE-FC02-07ER64494]
  3. US National Institute of Environmental Health Sciences Superfund Research Program [P42 ES004911]
  4. National Science Foundation [DBI-0328255]
  5. US Department of Agriculture National Institute of Food and Agriculture National Research Initiative [2008-35107-04542]
  6. National Institute of Health Research Project [U01 HL098961]
  7. Human Microbiome Project Demonstration Project [UH3 DK083993]
  8. US Department of Energy
  9. Direct For Biological Sciences
  10. Div Of Biological Infrastructure [0953738] Funding Source: National Science Foundation

向作者/读者索取更多资源

Ribosomal Database Project (RDP; http://rdp.cme.msu.edu/) provides the research community with aligned and annotated rRNA gene sequence data, along with tools to allow researchers to analyze their own rRNA gene sequences in the RDP framework. RDP data and tools are utilized in fields as diverse as human health, microbial ecology, environmental microbiology, nucleic acid chemistry, taxonomy and phylogenetics. In addition to aligned and annotated collections of bacterial and archaeal small subunit rRNA genes, RDP now includes a collection of fungal large subunit rRNA genes. RDP tools, including Classifier and Aligner, have been updated to work with this new fungal collection. The use of high-throughput sequencing to characterize environmental microbial populations has exploded in the past several years, and as sequence technologies have improved, the sizes of environmental datasets have increased. With release 11, RDP is providing an expanded set of tools to facilitate analysis of high-throughput data, including both single-stranded and paired-end reads. In addition, most tools are now available as open source packages for download and local use by researchers with high-volume needs or who would like to develop custom analysis pipelines.

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