SNiPlay: a web-based tool for detection, management and analysis of SNPs. Application to grapevine diversity projects

<p<Abstract</p< <p<Background</p< <p<High-throughput re-sequencing, new genotyping technologies and the availability of reference genomes allow the extensive characterization of Single Nucleotide Polymorphisms (SNPs) and insertion/deletion events (indels) in many plant species. The rapidly increasing amount of re-sequencing and genotyping data generated by large-scale genetic diversity projects requires the development of integrated bioinformatics tools able to efficiently manage, analyze, and combine these genetic data with genome structure and external data.</p< <p<Results</p< <p<In this context, we developed SNiPlay, a flexible, user-friendly and integrative web-based tool dedicated to polymorphism discovery and analysis. It integrates:</p< <p<1) a pipeline, freely accessible through the internet, combining existing softwares with new tools to detect SNPs and to compute different types of statistical indices and graphical layouts for SNP data. From standard sequence alignments, genotyping data or Sanger sequencing traces given as input, SNiPlay detects SNPs and indels events and outputs submission files for the design of Illumina's SNP chips. Subsequently, it sends sequences and genotyping data into a series of modules in charge of various processes: physical mapping to a reference genome, annotation (genomic position, intron/exon location, synonymous/non-synonymous substitutions), SNP frequency determination in user-defined groups, haplotype reconstruction and network, linkage disequilibrium evaluation, and diversity analysis (Pi, Watterson's Theta, Tajima's D).</p< <p<Furthermore, the pipeline allows the use of external data (such as phenotype, geographic origin, taxa, stratification) to define groups and compare statistical indices.</p< <p<2) a database storing polymorphisms, genotyping data and grapevine sequences released by public and private projects. It allows the user to retrieve SNPs using various filters (such as genomic position, missing data, polymorphism type, allele frequency), to compare SNP patterns between populations, and to export genotyping data or sequences in various formats.</p< <p<Conclusions</p< <p<Our experiments on grapevine genetic projects showed that SNiPlay allows geneticists to rapidly obtain advanced results in several key research areas of plant genetic diversity. Both the management and treatment of large amounts of SNP data are rendered considerably easier for end-users through automation and integration. Current developments are taking into account new advances in high-throughput technologies.</p< <p<SNiPlay is available at: <url<http://sniplay.cirad.fr/</url<.</p< Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Peros Jean-Pierre [verfasserIn] Doligez Agnès [verfasserIn] Bacilieri Roberto [verfasserIn] Le Cunff Loïc [verfasserIn] Nicolas Stéphane [verfasserIn] Dereeper Alexis [verfasserIn] Ruiz Manuel [verfasserIn] This Patrice [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2011

Übergeordnetes Werk:	In: BMC Bioinformatics - BMC, 2003, 12(2011), 1, p 134
Übergeordnetes Werk:	volume:12 ; year:2011 ; number:1, p 134

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1186/1471-2105-12-134

Katalog-ID:	DOAJ063707187

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allfields	10.1186/1471-2105-12-134 doi (DE-627)DOAJ063707187 (DE-599)DOAJacfd50c4abb04888bcdc1c26212715d6 DE-627 ger DE-627 rakwb eng R858-859.7 QH301-705.5 Peros Jean-Pierre verfasserin aut SNiPlay: a web-based tool for detection, management and analysis of SNPs. Application to grapevine diversity projects 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <p<Abstract</p< <p<Background</p< <p<High-throughput re-sequencing, new genotyping technologies and the availability of reference genomes allow the extensive characterization of Single Nucleotide Polymorphisms (SNPs) and insertion/deletion events (indels) in many plant species. The rapidly increasing amount of re-sequencing and genotyping data generated by large-scale genetic diversity projects requires the development of integrated bioinformatics tools able to efficiently manage, analyze, and combine these genetic data with genome structure and external data.</p< <p<Results</p< <p<In this context, we developed SNiPlay, a flexible, user-friendly and integrative web-based tool dedicated to polymorphism discovery and analysis. It integrates:</p< <p<1) a pipeline, freely accessible through the internet, combining existing softwares with new tools to detect SNPs and to compute different types of statistical indices and graphical layouts for SNP data. From standard sequence alignments, genotyping data or Sanger sequencing traces given as input, SNiPlay detects SNPs and indels events and outputs submission files for the design of Illumina's SNP chips. Subsequently, it sends sequences and genotyping data into a series of modules in charge of various processes: physical mapping to a reference genome, annotation (genomic position, intron/exon location, synonymous/non-synonymous substitutions), SNP frequency determination in user-defined groups, haplotype reconstruction and network, linkage disequilibrium evaluation, and diversity analysis (Pi, Watterson's Theta, Tajima's D).</p< <p<Furthermore, the pipeline allows the use of external data (such as phenotype, geographic origin, taxa, stratification) to define groups and compare statistical indices.</p< <p<2) a database storing polymorphisms, genotyping data and grapevine sequences released by public and private projects. It allows the user to retrieve SNPs using various filters (such as genomic position, missing data, polymorphism type, allele frequency), to compare SNP patterns between populations, and to export genotyping data or sequences in various formats.</p< <p<Conclusions</p< <p<Our experiments on grapevine genetic projects showed that SNiPlay allows geneticists to rapidly obtain advanced results in several key research areas of plant genetic diversity. Both the management and treatment of large amounts of SNP data are rendered considerably easier for end-users through automation and integration. Current developments are taking into account new advances in high-throughput technologies.</p< <p<SNiPlay is available at: <url<http://sniplay.cirad.fr/</url<.</p< Computer applications to medicine. Medical informatics Biology (General) Doligez Agnès verfasserin aut Bacilieri Roberto verfasserin aut Le Cunff Loïc verfasserin aut Nicolas Stéphane verfasserin aut Dereeper Alexis verfasserin aut Ruiz Manuel verfasserin aut This Patrice verfasserin aut In BMC Bioinformatics BMC, 2003 12(2011), 1, p 134 (DE-627)326644814 (DE-600)2041484-5 14712105 nnns volume:12 year:2011 number:1, p 134 https://doi.org/10.1186/1471-2105-12-134 kostenfrei https://doaj.org/article/acfd50c4abb04888bcdc1c26212715d6 kostenfrei http://www.biomedcentral.com/1471-2105/12/134 kostenfrei https://doaj.org/toc/1471-2105 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2011 1, p 134
spelling	10.1186/1471-2105-12-134 doi (DE-627)DOAJ063707187 (DE-599)DOAJacfd50c4abb04888bcdc1c26212715d6 DE-627 ger DE-627 rakwb eng R858-859.7 QH301-705.5 Peros Jean-Pierre verfasserin aut SNiPlay: a web-based tool for detection, management and analysis of SNPs. Application to grapevine diversity projects 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <p<Abstract</p< <p<Background</p< <p<High-throughput re-sequencing, new genotyping technologies and the availability of reference genomes allow the extensive characterization of Single Nucleotide Polymorphisms (SNPs) and insertion/deletion events (indels) in many plant species. The rapidly increasing amount of re-sequencing and genotyping data generated by large-scale genetic diversity projects requires the development of integrated bioinformatics tools able to efficiently manage, analyze, and combine these genetic data with genome structure and external data.</p< <p<Results</p< <p<In this context, we developed SNiPlay, a flexible, user-friendly and integrative web-based tool dedicated to polymorphism discovery and analysis. It integrates:</p< <p<1) a pipeline, freely accessible through the internet, combining existing softwares with new tools to detect SNPs and to compute different types of statistical indices and graphical layouts for SNP data. From standard sequence alignments, genotyping data or Sanger sequencing traces given as input, SNiPlay detects SNPs and indels events and outputs submission files for the design of Illumina's SNP chips. Subsequently, it sends sequences and genotyping data into a series of modules in charge of various processes: physical mapping to a reference genome, annotation (genomic position, intron/exon location, synonymous/non-synonymous substitutions), SNP frequency determination in user-defined groups, haplotype reconstruction and network, linkage disequilibrium evaluation, and diversity analysis (Pi, Watterson's Theta, Tajima's D).</p< <p<Furthermore, the pipeline allows the use of external data (such as phenotype, geographic origin, taxa, stratification) to define groups and compare statistical indices.</p< <p<2) a database storing polymorphisms, genotyping data and grapevine sequences released by public and private projects. It allows the user to retrieve SNPs using various filters (such as genomic position, missing data, polymorphism type, allele frequency), to compare SNP patterns between populations, and to export genotyping data or sequences in various formats.</p< <p<Conclusions</p< <p<Our experiments on grapevine genetic projects showed that SNiPlay allows geneticists to rapidly obtain advanced results in several key research areas of plant genetic diversity. Both the management and treatment of large amounts of SNP data are rendered considerably easier for end-users through automation and integration. Current developments are taking into account new advances in high-throughput technologies.</p< <p<SNiPlay is available at: <url<http://sniplay.cirad.fr/</url<.</p< Computer applications to medicine. Medical informatics Biology (General) Doligez Agnès verfasserin aut Bacilieri Roberto verfasserin aut Le Cunff Loïc verfasserin aut Nicolas Stéphane verfasserin aut Dereeper Alexis verfasserin aut Ruiz Manuel verfasserin aut This Patrice verfasserin aut In BMC Bioinformatics BMC, 2003 12(2011), 1, p 134 (DE-627)326644814 (DE-600)2041484-5 14712105 nnns volume:12 year:2011 number:1, p 134 https://doi.org/10.1186/1471-2105-12-134 kostenfrei https://doaj.org/article/acfd50c4abb04888bcdc1c26212715d6 kostenfrei http://www.biomedcentral.com/1471-2105/12/134 kostenfrei https://doaj.org/toc/1471-2105 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2011 1, p 134
allfields_unstemmed	10.1186/1471-2105-12-134 doi (DE-627)DOAJ063707187 (DE-599)DOAJacfd50c4abb04888bcdc1c26212715d6 DE-627 ger DE-627 rakwb eng R858-859.7 QH301-705.5 Peros Jean-Pierre verfasserin aut SNiPlay: a web-based tool for detection, management and analysis of SNPs. Application to grapevine diversity projects 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <p<Abstract</p< <p<Background</p< <p<High-throughput re-sequencing, new genotyping technologies and the availability of reference genomes allow the extensive characterization of Single Nucleotide Polymorphisms (SNPs) and insertion/deletion events (indels) in many plant species. The rapidly increasing amount of re-sequencing and genotyping data generated by large-scale genetic diversity projects requires the development of integrated bioinformatics tools able to efficiently manage, analyze, and combine these genetic data with genome structure and external data.</p< <p<Results</p< <p<In this context, we developed SNiPlay, a flexible, user-friendly and integrative web-based tool dedicated to polymorphism discovery and analysis. It integrates:</p< <p<1) a pipeline, freely accessible through the internet, combining existing softwares with new tools to detect SNPs and to compute different types of statistical indices and graphical layouts for SNP data. From standard sequence alignments, genotyping data or Sanger sequencing traces given as input, SNiPlay detects SNPs and indels events and outputs submission files for the design of Illumina's SNP chips. Subsequently, it sends sequences and genotyping data into a series of modules in charge of various processes: physical mapping to a reference genome, annotation (genomic position, intron/exon location, synonymous/non-synonymous substitutions), SNP frequency determination in user-defined groups, haplotype reconstruction and network, linkage disequilibrium evaluation, and diversity analysis (Pi, Watterson's Theta, Tajima's D).</p< <p<Furthermore, the pipeline allows the use of external data (such as phenotype, geographic origin, taxa, stratification) to define groups and compare statistical indices.</p< <p<2) a database storing polymorphisms, genotyping data and grapevine sequences released by public and private projects. It allows the user to retrieve SNPs using various filters (such as genomic position, missing data, polymorphism type, allele frequency), to compare SNP patterns between populations, and to export genotyping data or sequences in various formats.</p< <p<Conclusions</p< <p<Our experiments on grapevine genetic projects showed that SNiPlay allows geneticists to rapidly obtain advanced results in several key research areas of plant genetic diversity. Both the management and treatment of large amounts of SNP data are rendered considerably easier for end-users through automation and integration. Current developments are taking into account new advances in high-throughput technologies.</p< <p<SNiPlay is available at: <url<http://sniplay.cirad.fr/</url<.</p< Computer applications to medicine. Medical informatics Biology (General) Doligez Agnès verfasserin aut Bacilieri Roberto verfasserin aut Le Cunff Loïc verfasserin aut Nicolas Stéphane verfasserin aut Dereeper Alexis verfasserin aut Ruiz Manuel verfasserin aut This Patrice verfasserin aut In BMC Bioinformatics BMC, 2003 12(2011), 1, p 134 (DE-627)326644814 (DE-600)2041484-5 14712105 nnns volume:12 year:2011 number:1, p 134 https://doi.org/10.1186/1471-2105-12-134 kostenfrei https://doaj.org/article/acfd50c4abb04888bcdc1c26212715d6 kostenfrei http://www.biomedcentral.com/1471-2105/12/134 kostenfrei https://doaj.org/toc/1471-2105 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2011 1, p 134
allfieldsGer	10.1186/1471-2105-12-134 doi (DE-627)DOAJ063707187 (DE-599)DOAJacfd50c4abb04888bcdc1c26212715d6 DE-627 ger DE-627 rakwb eng R858-859.7 QH301-705.5 Peros Jean-Pierre verfasserin aut SNiPlay: a web-based tool for detection, management and analysis of SNPs. Application to grapevine diversity projects 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <p<Abstract</p< <p<Background</p< <p<High-throughput re-sequencing, new genotyping technologies and the availability of reference genomes allow the extensive characterization of Single Nucleotide Polymorphisms (SNPs) and insertion/deletion events (indels) in many plant species. The rapidly increasing amount of re-sequencing and genotyping data generated by large-scale genetic diversity projects requires the development of integrated bioinformatics tools able to efficiently manage, analyze, and combine these genetic data with genome structure and external data.</p< <p<Results</p< <p<In this context, we developed SNiPlay, a flexible, user-friendly and integrative web-based tool dedicated to polymorphism discovery and analysis. It integrates:</p< <p<1) a pipeline, freely accessible through the internet, combining existing softwares with new tools to detect SNPs and to compute different types of statistical indices and graphical layouts for SNP data. From standard sequence alignments, genotyping data or Sanger sequencing traces given as input, SNiPlay detects SNPs and indels events and outputs submission files for the design of Illumina's SNP chips. Subsequently, it sends sequences and genotyping data into a series of modules in charge of various processes: physical mapping to a reference genome, annotation (genomic position, intron/exon location, synonymous/non-synonymous substitutions), SNP frequency determination in user-defined groups, haplotype reconstruction and network, linkage disequilibrium evaluation, and diversity analysis (Pi, Watterson's Theta, Tajima's D).</p< <p<Furthermore, the pipeline allows the use of external data (such as phenotype, geographic origin, taxa, stratification) to define groups and compare statistical indices.</p< <p<2) a database storing polymorphisms, genotyping data and grapevine sequences released by public and private projects. It allows the user to retrieve SNPs using various filters (such as genomic position, missing data, polymorphism type, allele frequency), to compare SNP patterns between populations, and to export genotyping data or sequences in various formats.</p< <p<Conclusions</p< <p<Our experiments on grapevine genetic projects showed that SNiPlay allows geneticists to rapidly obtain advanced results in several key research areas of plant genetic diversity. Both the management and treatment of large amounts of SNP data are rendered considerably easier for end-users through automation and integration. Current developments are taking into account new advances in high-throughput technologies.</p< <p<SNiPlay is available at: <url<http://sniplay.cirad.fr/</url<.</p< Computer applications to medicine. Medical informatics Biology (General) Doligez Agnès verfasserin aut Bacilieri Roberto verfasserin aut Le Cunff Loïc verfasserin aut Nicolas Stéphane verfasserin aut Dereeper Alexis verfasserin aut Ruiz Manuel verfasserin aut This Patrice verfasserin aut In BMC Bioinformatics BMC, 2003 12(2011), 1, p 134 (DE-627)326644814 (DE-600)2041484-5 14712105 nnns volume:12 year:2011 number:1, p 134 https://doi.org/10.1186/1471-2105-12-134 kostenfrei https://doaj.org/article/acfd50c4abb04888bcdc1c26212715d6 kostenfrei http://www.biomedcentral.com/1471-2105/12/134 kostenfrei https://doaj.org/toc/1471-2105 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2011 1, p 134
allfieldsSound	10.1186/1471-2105-12-134 doi (DE-627)DOAJ063707187 (DE-599)DOAJacfd50c4abb04888bcdc1c26212715d6 DE-627 ger DE-627 rakwb eng R858-859.7 QH301-705.5 Peros Jean-Pierre verfasserin aut SNiPlay: a web-based tool for detection, management and analysis of SNPs. Application to grapevine diversity projects 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <p<Abstract</p< <p<Background</p< <p<High-throughput re-sequencing, new genotyping technologies and the availability of reference genomes allow the extensive characterization of Single Nucleotide Polymorphisms (SNPs) and insertion/deletion events (indels) in many plant species. The rapidly increasing amount of re-sequencing and genotyping data generated by large-scale genetic diversity projects requires the development of integrated bioinformatics tools able to efficiently manage, analyze, and combine these genetic data with genome structure and external data.</p< <p<Results</p< <p<In this context, we developed SNiPlay, a flexible, user-friendly and integrative web-based tool dedicated to polymorphism discovery and analysis. It integrates:</p< <p<1) a pipeline, freely accessible through the internet, combining existing softwares with new tools to detect SNPs and to compute different types of statistical indices and graphical layouts for SNP data. From standard sequence alignments, genotyping data or Sanger sequencing traces given as input, SNiPlay detects SNPs and indels events and outputs submission files for the design of Illumina's SNP chips. Subsequently, it sends sequences and genotyping data into a series of modules in charge of various processes: physical mapping to a reference genome, annotation (genomic position, intron/exon location, synonymous/non-synonymous substitutions), SNP frequency determination in user-defined groups, haplotype reconstruction and network, linkage disequilibrium evaluation, and diversity analysis (Pi, Watterson's Theta, Tajima's D).</p< <p<Furthermore, the pipeline allows the use of external data (such as phenotype, geographic origin, taxa, stratification) to define groups and compare statistical indices.</p< <p<2) a database storing polymorphisms, genotyping data and grapevine sequences released by public and private projects. It allows the user to retrieve SNPs using various filters (such as genomic position, missing data, polymorphism type, allele frequency), to compare SNP patterns between populations, and to export genotyping data or sequences in various formats.</p< <p<Conclusions</p< <p<Our experiments on grapevine genetic projects showed that SNiPlay allows geneticists to rapidly obtain advanced results in several key research areas of plant genetic diversity. Both the management and treatment of large amounts of SNP data are rendered considerably easier for end-users through automation and integration. Current developments are taking into account new advances in high-throughput technologies.</p< <p<SNiPlay is available at: <url<http://sniplay.cirad.fr/</url<.</p< Computer applications to medicine. Medical informatics Biology (General) Doligez Agnès verfasserin aut Bacilieri Roberto verfasserin aut Le Cunff Loïc verfasserin aut Nicolas Stéphane verfasserin aut Dereeper Alexis verfasserin aut Ruiz Manuel verfasserin aut This Patrice verfasserin aut In BMC Bioinformatics BMC, 2003 12(2011), 1, p 134 (DE-627)326644814 (DE-600)2041484-5 14712105 nnns volume:12 year:2011 number:1, p 134 https://doi.org/10.1186/1471-2105-12-134 kostenfrei https://doaj.org/article/acfd50c4abb04888bcdc1c26212715d6 kostenfrei http://www.biomedcentral.com/1471-2105/12/134 kostenfrei https://doaj.org/toc/1471-2105 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2011 1, p 134
language	English
source	In BMC Bioinformatics 12(2011), 1, p 134 volume:12 year:2011 number:1, p 134
sourceStr	In BMC Bioinformatics 12(2011), 1, p 134 volume:12 year:2011 number:1, p 134
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Computer applications to medicine. Medical informatics Biology (General)
isfreeaccess_bool	true
container_title	BMC Bioinformatics
authorswithroles_txt_mv	Peros Jean-Pierre @@aut@@ Doligez Agnès @@aut@@ Bacilieri Roberto @@aut@@ Le Cunff Loïc @@aut@@ Nicolas Stéphane @@aut@@ Dereeper Alexis @@aut@@ Ruiz Manuel @@aut@@ This Patrice @@aut@@
publishDateDaySort_date	2011-01-01T00:00:00Z
hierarchy_top_id	326644814
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language_de	englisch
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Application to grapevine diversity projects</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2011</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a"><p<Abstract</p< <p<Background</p< <p<High-throughput re-sequencing, new genotyping technologies and the availability of reference genomes allow the extensive characterization of Single Nucleotide Polymorphisms (SNPs) and insertion/deletion events (indels) in many plant species. The rapidly increasing amount of re-sequencing and genotyping data generated by large-scale genetic diversity projects requires the development of integrated bioinformatics tools able to efficiently manage, analyze, and combine these genetic data with genome structure and external data.</p< <p<Results</p< <p<In this context, we developed SNiPlay, a flexible, user-friendly and integrative web-based tool dedicated to polymorphism discovery and analysis. It integrates:</p< <p<1) a pipeline, freely accessible through the internet, combining existing softwares with new tools to detect SNPs and to compute different types of statistical indices and graphical layouts for SNP data. From standard sequence alignments, genotyping data or Sanger sequencing traces given as input, SNiPlay detects SNPs and indels events and outputs submission files for the design of Illumina's SNP chips. 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callnumber-first	R - Medicine
author	Peros Jean-Pierre
spellingShingle	Peros Jean-Pierre misc R858-859.7 misc QH301-705.5 misc Computer applications to medicine. Medical informatics misc Biology (General) SNiPlay: a web-based tool for detection, management and analysis of SNPs. Application to grapevine diversity projects
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topic_title	R858-859.7 QH301-705.5 SNiPlay: a web-based tool for detection, management and analysis of SNPs. Application to grapevine diversity projects
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title	SNiPlay: a web-based tool for detection, management and analysis of SNPs. Application to grapevine diversity projects
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title_full	SNiPlay: a web-based tool for detection, management and analysis of SNPs. Application to grapevine diversity projects
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title_sort	sniplay: a web-based tool for detection, management and analysis of snps. application to grapevine diversity projects
callnumber	R858-859.7
title_auth	SNiPlay: a web-based tool for detection, management and analysis of SNPs. Application to grapevine diversity projects
abstract	<p<Abstract</p< <p<Background</p< <p<High-throughput re-sequencing, new genotyping technologies and the availability of reference genomes allow the extensive characterization of Single Nucleotide Polymorphisms (SNPs) and insertion/deletion events (indels) in many plant species. The rapidly increasing amount of re-sequencing and genotyping data generated by large-scale genetic diversity projects requires the development of integrated bioinformatics tools able to efficiently manage, analyze, and combine these genetic data with genome structure and external data.</p< <p<Results</p< <p<In this context, we developed SNiPlay, a flexible, user-friendly and integrative web-based tool dedicated to polymorphism discovery and analysis. It integrates:</p< <p<1) a pipeline, freely accessible through the internet, combining existing softwares with new tools to detect SNPs and to compute different types of statistical indices and graphical layouts for SNP data. From standard sequence alignments, genotyping data or Sanger sequencing traces given as input, SNiPlay detects SNPs and indels events and outputs submission files for the design of Illumina's SNP chips. Subsequently, it sends sequences and genotyping data into a series of modules in charge of various processes: physical mapping to a reference genome, annotation (genomic position, intron/exon location, synonymous/non-synonymous substitutions), SNP frequency determination in user-defined groups, haplotype reconstruction and network, linkage disequilibrium evaluation, and diversity analysis (Pi, Watterson's Theta, Tajima's D).</p< <p<Furthermore, the pipeline allows the use of external data (such as phenotype, geographic origin, taxa, stratification) to define groups and compare statistical indices.</p< <p<2) a database storing polymorphisms, genotyping data and grapevine sequences released by public and private projects. It allows the user to retrieve SNPs using various filters (such as genomic position, missing data, polymorphism type, allele frequency), to compare SNP patterns between populations, and to export genotyping data or sequences in various formats.</p< <p<Conclusions</p< <p<Our experiments on grapevine genetic projects showed that SNiPlay allows geneticists to rapidly obtain advanced results in several key research areas of plant genetic diversity. Both the management and treatment of large amounts of SNP data are rendered considerably easier for end-users through automation and integration. Current developments are taking into account new advances in high-throughput technologies.</p< <p<SNiPlay is available at: <url<http://sniplay.cirad.fr/</url<.</p<
abstractGer	<p<Abstract</p< <p<Background</p< <p<High-throughput re-sequencing, new genotyping technologies and the availability of reference genomes allow the extensive characterization of Single Nucleotide Polymorphisms (SNPs) and insertion/deletion events (indels) in many plant species. The rapidly increasing amount of re-sequencing and genotyping data generated by large-scale genetic diversity projects requires the development of integrated bioinformatics tools able to efficiently manage, analyze, and combine these genetic data with genome structure and external data.</p< <p<Results</p< <p<In this context, we developed SNiPlay, a flexible, user-friendly and integrative web-based tool dedicated to polymorphism discovery and analysis. It integrates:</p< <p<1) a pipeline, freely accessible through the internet, combining existing softwares with new tools to detect SNPs and to compute different types of statistical indices and graphical layouts for SNP data. From standard sequence alignments, genotyping data or Sanger sequencing traces given as input, SNiPlay detects SNPs and indels events and outputs submission files for the design of Illumina's SNP chips. Subsequently, it sends sequences and genotyping data into a series of modules in charge of various processes: physical mapping to a reference genome, annotation (genomic position, intron/exon location, synonymous/non-synonymous substitutions), SNP frequency determination in user-defined groups, haplotype reconstruction and network, linkage disequilibrium evaluation, and diversity analysis (Pi, Watterson's Theta, Tajima's D).</p< <p<Furthermore, the pipeline allows the use of external data (such as phenotype, geographic origin, taxa, stratification) to define groups and compare statistical indices.</p< <p<2) a database storing polymorphisms, genotyping data and grapevine sequences released by public and private projects. It allows the user to retrieve SNPs using various filters (such as genomic position, missing data, polymorphism type, allele frequency), to compare SNP patterns between populations, and to export genotyping data or sequences in various formats.</p< <p<Conclusions</p< <p<Our experiments on grapevine genetic projects showed that SNiPlay allows geneticists to rapidly obtain advanced results in several key research areas of plant genetic diversity. Both the management and treatment of large amounts of SNP data are rendered considerably easier for end-users through automation and integration. Current developments are taking into account new advances in high-throughput technologies.</p< <p<SNiPlay is available at: <url<http://sniplay.cirad.fr/</url<.</p<
abstract_unstemmed	<p<Abstract</p< <p<Background</p< <p<High-throughput re-sequencing, new genotyping technologies and the availability of reference genomes allow the extensive characterization of Single Nucleotide Polymorphisms (SNPs) and insertion/deletion events (indels) in many plant species. The rapidly increasing amount of re-sequencing and genotyping data generated by large-scale genetic diversity projects requires the development of integrated bioinformatics tools able to efficiently manage, analyze, and combine these genetic data with genome structure and external data.</p< <p<Results</p< <p<In this context, we developed SNiPlay, a flexible, user-friendly and integrative web-based tool dedicated to polymorphism discovery and analysis. It integrates:</p< <p<1) a pipeline, freely accessible through the internet, combining existing softwares with new tools to detect SNPs and to compute different types of statistical indices and graphical layouts for SNP data. From standard sequence alignments, genotyping data or Sanger sequencing traces given as input, SNiPlay detects SNPs and indels events and outputs submission files for the design of Illumina's SNP chips. Subsequently, it sends sequences and genotyping data into a series of modules in charge of various processes: physical mapping to a reference genome, annotation (genomic position, intron/exon location, synonymous/non-synonymous substitutions), SNP frequency determination in user-defined groups, haplotype reconstruction and network, linkage disequilibrium evaluation, and diversity analysis (Pi, Watterson's Theta, Tajima's D).</p< <p<Furthermore, the pipeline allows the use of external data (such as phenotype, geographic origin, taxa, stratification) to define groups and compare statistical indices.</p< <p<2) a database storing polymorphisms, genotyping data and grapevine sequences released by public and private projects. It allows the user to retrieve SNPs using various filters (such as genomic position, missing data, polymorphism type, allele frequency), to compare SNP patterns between populations, and to export genotyping data or sequences in various formats.</p< <p<Conclusions</p< <p<Our experiments on grapevine genetic projects showed that SNiPlay allows geneticists to rapidly obtain advanced results in several key research areas of plant genetic diversity. Both the management and treatment of large amounts of SNP data are rendered considerably easier for end-users through automation and integration. Current developments are taking into account new advances in high-throughput technologies.</p< <p<SNiPlay is available at: <url<http://sniplay.cirad.fr/</url<.</p<
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title_short	SNiPlay: a web-based tool for detection, management and analysis of SNPs. Application to grapevine diversity projects
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Application to grapevine diversity projects</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2011</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a"><p<Abstract</p< <p<Background</p< <p<High-throughput re-sequencing, new genotyping technologies and the availability of reference genomes allow the extensive characterization of Single Nucleotide Polymorphisms (SNPs) and insertion/deletion events (indels) in many plant species. The rapidly increasing amount of re-sequencing and genotyping data generated by large-scale genetic diversity projects requires the development of integrated bioinformatics tools able to efficiently manage, analyze, and combine these genetic data with genome structure and external data.</p< <p<Results</p< <p<In this context, we developed SNiPlay, a flexible, user-friendly and integrative web-based tool dedicated to polymorphism discovery and analysis. It integrates:</p< <p<1) a pipeline, freely accessible through the internet, combining existing softwares with new tools to detect SNPs and to compute different types of statistical indices and graphical layouts for SNP data. From standard sequence alignments, genotyping data or Sanger sequencing traces given as input, SNiPlay detects SNPs and indels events and outputs submission files for the design of Illumina's SNP chips. Subsequently, it sends sequences and genotyping data into a series of modules in charge of various processes: physical mapping to a reference genome, annotation (genomic position, intron/exon location, synonymous/non-synonymous substitutions), SNP frequency determination in user-defined groups, haplotype reconstruction and network, linkage disequilibrium evaluation, and diversity analysis (Pi, Watterson's Theta, Tajima's D).</p< <p<Furthermore, the pipeline allows the use of external data (such as phenotype, geographic origin, taxa, stratification) to define groups and compare statistical indices.</p< <p<2) a database storing polymorphisms, genotyping data and grapevine sequences released by public and private projects. It allows the user to retrieve SNPs using various filters (such as genomic position, missing data, polymorphism type, allele frequency), to compare SNP patterns between populations, and to export genotyping data or sequences in various formats.</p< <p<Conclusions</p< <p<Our experiments on grapevine genetic projects showed that SNiPlay allows geneticists to rapidly obtain advanced results in several key research areas of plant genetic diversity. Both the management and treatment of large amounts of SNP data are rendered considerably easier for end-users through automation and integration. Current developments are taking into account new advances in high-throughput technologies.</p< <p<SNiPlay is available at: <url<http://sniplay.cirad.fr/</url<.</p<</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Computer applications to medicine. 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SNiPlay: a web-based tool for detection, management and analysis of SNPs. Application to grapevine diversity projects

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