Construction and Analysis of High-Density Linkage Map Using High-Throughput Sequencing Data
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{"title"=>"Construction and analysis of high-density linkage map using high-throughput sequencing data", "type"=>"journal", "authors"=>[{"first_name"=>"Dongyuan", "last_name"=>"Liu", "scopus_author_id"=>"26028915000"}, {"first_name"=>"Chouxian", "last_name"=>"Ma", "scopus_author_id"=>"55861340700"}, {"first_name"=>"Weiguo", "last_name"=>"Hong", "scopus_author_id"=>"55625524400"}, {"first_name"=>"Long", "last_name"=>"Huang", "scopus_author_id"=>"56208910300"}, {"first_name"=>"Min", "last_name"=>"Liu", "scopus_author_id"=>"56208907200"}, {"first_name"=>"Hui", "last_name"=>"Liu", "scopus_author_id"=>"56861898700"}, {"first_name"=>"Huaping", "last_name"=>"Zeng", "scopus_author_id"=>"55625205200"}, {"first_name"=>"Dejing", "last_name"=>"Deng", "scopus_author_id"=>"37048570700"}, {"first_name"=>"Huaigen", "last_name"=>"Xin", "scopus_author_id"=>"55861521800"}, {"first_name"=>"Jun", "last_name"=>"Song", "scopus_author_id"=>"57199024796"}, {"first_name"=>"Chunhua", "last_name"=>"Xu", "scopus_author_id"=>"55625676100"}, {"first_name"=>"Xiaowen", "last_name"=>"Sun", "scopus_author_id"=>"55551946900"}, {"first_name"=>"Xilin", "last_name"=>"Hou", "scopus_author_id"=>"10043420000"}, {"first_name"=>"Xiaowu", "last_name"=>"Wang", "scopus_author_id"=>"8338465300"}, {"first_name"=>"Hongkun", "last_name"=>"Zheng", "scopus_author_id"=>"7403440857"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"sgr"=>"84902590946", "doi"=>"10.1371/journal.pone.0098855", "pui"=>"373337423", "pmid"=>"24905985", "scopus"=>"2-s2.0-84902590946", "issn"=>"19326203", "isbn"=>"1932-6203"}, "id"=>"d69a2212-6776-3d18-8326-d1324e819ac1", "abstract"=>"Linkage maps enable the study of important biological questions. The construction of high-density linkage maps appears more feasible since the advent of next-generation sequencing (NGS), which eases SNP discovery and high-throughput genotyping of large population. However, the marker number explosion and genotyping errors from NGS data challenge the computational efficiency and linkage map quality of linkage study methods. Here we report the HighMap method for constructing high-density linkage maps from NGS data. HighMap employs an iterative ordering and error correction strategy based on a k-nearest neighbor algorithm and a Monte Carlo multipoint maximum likelihood algorithm. Simulation study shows HighMap can create a linkage map with three times as many markers as ordering-only methods while offering more accurate marker orders and stable genetic distances. Using HighMap, we constructed a common carp linkage map with 10,004 markers. The singleton rate was less than one-ninth of that generated by JoinMap4.1. Its total map distance was 5,908 cM, consistent with reports on low-density maps. HighMap is an efficient method for constructing high-density, high-quality linkage maps from high-throughput population NGS data. It will facilitate genome assembling, comparative genomic analysis, and QTL studies. HighMap is available at http://highmap.biomarker.com.cn/.", "link"=>"http://www.mendeley.com/research/construction-analysis-highdensity-linkage-map-using-highthroughput-sequencing-data-1", "reader_count"=>90, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>4, "Researcher"=>30, "Student > Doctoral Student"=>5, "Student > Ph. D. Student"=>22, "Student > Postgraduate"=>5, "Student > Master"=>14, "Other"=>3, "Student > Bachelor"=>3, "Lecturer"=>2, "Professor"=>2}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>4, "Researcher"=>30, "Student > Doctoral Student"=>5, "Student > Ph. D. Student"=>22, "Student > Postgraduate"=>5, "Student > Master"=>14, "Other"=>3, "Student > Bachelor"=>3, "Lecturer"=>2, "Professor"=>2}, "reader_count_by_subject_area"=>{"Unspecified"=>2, "Engineering"=>1, "Environmental Science"=>1, "Biochemistry, Genetics and Molecular Biology"=>18, "Agricultural and Biological Sciences"=>66, "Computer Science"=>2}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>66}, "Computer Science"=>{"Computer Science"=>2}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>18}, "Unspecified"=>{"Unspecified"=>2}, "Environmental Science"=>{"Environmental Science"=>1}}, "reader_count_by_country"=>{"Colombia"=>1, "Sweden"=>1, "United States"=>2, "Brazil"=>3, "Thailand"=>1, "France"=>3, "Spain"=>1}, "group_count"=>4}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1525232"], "description"=>"<p>The X-axis represents marker numbers. The Y-axis represents Spearman rank correlation coefficient between estimated map marker order and true marker location for A, B and C, singleton rates for D, E and F, estimated genetic map distances for G, H and I, respectively.</p>", "links"=>[], "tags"=>["agriculture", "Agricultural biotechnology", "crops", "Computational biology", "genetics", "genomics", "Information technology", "enhancement"], "article_id"=>1049453, "categories"=>["Biological Sciences"], "users"=>["Dongyuan Liu", "Chouxian Ma", "Weiguo Hong", "Long Huang", "Min Liu", "Hui Liu", "Huaping Zeng", "Dejing Deng", "Huaigen Xin", "Jun Song", "Chunhua Xu", "Xiaowen Sun", "Xilin Hou", "Xiaowu Wang", "Hongkun Zheng"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098855.g002", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_NGS_data_utilization_enhancement_by_HighMap_/1049453", "title"=>"NGS data utilization enhancement by HighMap.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-06-06 03:12:42"}
  • {"files"=>["https://ndownloader.figshare.com/files/1525233"], "description"=>"<p>Capability of missing imputation and error correction of HighMap.</p>", "links"=>[], "tags"=>["agriculture", "Agricultural biotechnology", "crops", "Computational biology", "genetics", "genomics", "Information technology", "imputation", "correction"], "article_id"=>1049454, "categories"=>["Biological Sciences"], "users"=>["Dongyuan Liu", "Chouxian Ma", "Weiguo Hong", "Long Huang", "Min Liu", "Hui Liu", "Huaping Zeng", "Dejing Deng", "Huaigen Xin", "Jun Song", "Chunhua Xu", "Xiaowen Sun", "Xilin Hou", "Xiaowu Wang", "Hongkun Zheng"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098855.t001", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Capability_of_missing_imputation_and_error_correction_of_HighMap_/1049454", "title"=>"Capability of missing imputation and error correction of HighMap.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-06-06 03:12:42"}
  • {"files"=>["https://ndownloader.figshare.com/files/1525231"], "description"=>"<p>A: The single-linkage clustering algorithm was used to partition the marker loci into linkage groups based on a pairwise modified independence LOD score for the recombination frequency. B and B': The ordering module combines Gibbs sampling, spatial sampling, and simulated annealing algorithm to order markers and estimate map distances. C: The error correction module identified singletons according to parental contribution of genotypes and eliminated them from the data using <i>k</i>-nearest neighbor algorithm. To order markers correctly, the processes of ordering and error correction were carried out iteratively. D: Heat maps and haplotype maps were constructed to evaluate map quality.</p>", "links"=>[], "tags"=>["agriculture", "Agricultural biotechnology", "crops", "Computational biology", "genetics", "genomics", "Information technology", "highmap"], "article_id"=>1049452, "categories"=>["Biological Sciences"], "users"=>["Dongyuan Liu", "Chouxian Ma", "Weiguo Hong", "Long Huang", "Min Liu", "Hui Liu", "Huaping Zeng", "Dejing Deng", "Huaigen Xin", "Jun Song", "Chunhua Xu", "Xiaowen Sun", "Xilin Hou", "Xiaowu Wang", "Hongkun Zheng"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098855.g001", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Modules_of_HighMap_algorithm_/1049452", "title"=>"Modules of HighMap algorithm.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-06-06 03:12:42"}
  • {"files"=>["https://ndownloader.figshare.com/files/1525254", "https://ndownloader.figshare.com/files/1525255", "https://ndownloader.figshare.com/files/1525256", "https://ndownloader.figshare.com/files/1525257", "https://ndownloader.figshare.com/files/1525261", "https://ndownloader.figshare.com/files/1525262", "https://ndownloader.figshare.com/files/1525263", "https://ndownloader.figshare.com/files/1525264", "https://ndownloader.figshare.com/files/1525265"], "description"=>"<div><p>Linkage maps enable the study of important biological questions. The construction of high-density linkage maps appears more feasible since the advent of next-generation sequencing (NGS), which eases SNP discovery and high-throughput genotyping of large population. However, the marker number explosion and genotyping errors from NGS data challenge the computational efficiency and linkage map quality of linkage study methods. Here we report the HighMap method for constructing high-density linkage maps from NGS data. HighMap employs an iterative ordering and error correction strategy based on a k-nearest neighbor algorithm and a Monte Carlo multipoint maximum likelihood algorithm. Simulation study shows HighMap can create a linkage map with three times as many markers as ordering-only methods while offering more accurate marker orders and stable genetic distances. Using HighMap, we constructed a common carp linkage map with 10,004 markers. The singleton rate was less than one-ninth of that generated by JoinMap4.1. Its total map distance was 5,908 cM, consistent with reports on low-density maps. HighMap is an efficient method for constructing high-density, high-quality linkage maps from high-throughput population NGS data. It will facilitate genome assembling, comparative genomic analysis, and QTL studies. HighMap is available at <a href=\"http://highmap.biomarker.com.cn/\" target=\"_blank\">http://highmap.biomarker.com.cn/</a>.</p></div>", "links"=>[], "tags"=>["agriculture", "Agricultural biotechnology", "crops", "Computational biology", "genetics", "genomics", "Information technology", "high-density", "linkage", "high-throughput", "sequencing"], "article_id"=>1049468, "categories"=>["Biological Sciences"], "users"=>["Dongyuan Liu", "Chouxian Ma", "Weiguo Hong", "Long Huang", "Min Liu", "Hui Liu", "Huaping Zeng", "Dejing Deng", "Huaigen Xin", "Jun Song", "Chunhua Xu", "Xiaowen Sun", "Xilin Hou", "Xiaowu Wang", "Hongkun Zheng"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0098855.s001", "https://dx.doi.org/10.1371/journal.pone.0098855.s002", "https://dx.doi.org/10.1371/journal.pone.0098855.s003", "https://dx.doi.org/10.1371/journal.pone.0098855.s004", "https://dx.doi.org/10.1371/journal.pone.0098855.s005", "https://dx.doi.org/10.1371/journal.pone.0098855.s006", "https://dx.doi.org/10.1371/journal.pone.0098855.s007", "https://dx.doi.org/10.1371/journal.pone.0098855.s008", "https://dx.doi.org/10.1371/journal.pone.0098855.s009"], "stats"=>{"downloads"=>16, "page_views"=>22, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Construction_and_Analysis_of_High_Density_Linkage_Map_Using_High_Throughput_Sequencing_Data_/1049468", "title"=>"Construction and Analysis of High-Density Linkage Map Using High-Throughput Sequencing Data", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2014-06-06 03:12:42"}
  • {"files"=>["https://ndownloader.figshare.com/files/1525234"], "description"=>"<p>Genotyping error and missing rates of different segregation patterns in NGS.</p>", "links"=>[], "tags"=>["agriculture", "Agricultural biotechnology", "crops", "Computational biology", "genetics", "genomics", "Information technology", "rates", "segregation", "patterns"], "article_id"=>1049455, "categories"=>["Biological Sciences"], "users"=>["Dongyuan Liu", "Chouxian Ma", "Weiguo Hong", "Long Huang", "Min Liu", "Hui Liu", "Huaping Zeng", "Dejing Deng", "Huaigen Xin", "Jun Song", "Chunhua Xu", "Xiaowen Sun", "Xilin Hou", "Xiaowu Wang", "Hongkun Zheng"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0098855.t002", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Genotyping_error_and_missing_rates_of_different_segregation_patterns_in_NGS_/1049455", "title"=>"Genotyping error and missing rates of different segregation patterns in NGS.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-06-06 03:12:42"}

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