4.8 Article

An integrated framework for discovery and genotyping of genomic variants from high-throughput sequencing experiments

期刊

NUCLEIC ACIDS RESEARCH
卷 42, 期 6, 页码 -

出版社

OXFORD UNIV PRESS
DOI: 10.1093/nar/gkt1381

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资金

  1. International Center for Tropical Agriculture (CIAT)
  2. National Science Foundation (NSF) [0965420]
  3. Agentschap voor Innovatie door Wetenschap en Technologie (IWT) Flanders [SBO IWT50148, IWT90043]
  4. European Commission (EC) 7th Framework program (NEMO project)
  5. Katholieke Universiteit Leuven (KU Leuven) Industrieel Onderzoeksfonds (IOF) Knowledge platform [IKP/10/002 [ZKC1836]]
  6. Bijzonder Onderzoeksfonds (BOF) Program
  7. European Research Council (ERC) [241426]
  8. Vlaams Instituut voor Biotechnologie (VIB)
  9. Fonds Wetenschappelijk Onderzoek (FWO) Vlaanderen
  10. Odysseus program
  11. European Molecular Biology Organization (EMBO) International Youth Initiative Program (YIP)
  12. International Center for Tropical Agriculture (CIAT) Core Funding
  13. Direct For Biological Sciences
  14. Division Of Integrative Organismal Systems [0965420] Funding Source: National Science Foundation

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Recent advances in high-throughput sequencing (HTS) technologies and computing capacity have produced unprecedented amounts of genomic data that have unraveled the genetics of phenotypic variability in several species. However, operating and integrating current software tools for data analysis still require important investments in highly skilled personnel. Developing accurate, efficient and user-friendly software packages for HTS data analysis will lead to a more rapid discovery of genomic elements relevant to medical, agricultural and industrial applications. We therefore developed Next-Generation Sequencing Eclipse Plug-in (NGSEP), a new software tool for integrated, efficient and user-friendly detection of single nucleotide variants (SNVs), indels and copy number variants (CNVs). NGSEP includes modules for read alignment, sorting, merging, functional annotation of variants, filtering and quality statistics. Analysis of sequencing experiments in yeast, rice and human samples shows that NGSEP has superior accuracy and efficiency, compared with currently available packages for variants detection. We also show that only a comprehensive and accurate identification of repeat regions and CNVs allows researchers to properly separate SNVs from differences between copies of repeat elements. We expect that NGSEP will become a strong support tool to empower the analysis of sequencing data in a wide range of research projects on different species.

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