Local Genealogies in a Linear Mixed Model for Genome-Wide Association Mapping in Complex Pedigreed Populations
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{"title"=>"Local genealogies in a linear mixed model for genome-wide association mapping in complex pedigreed populations", "type"=>"journal", "authors"=>[{"first_name"=>"Goutam", "last_name"=>"Sahana", "scopus_author_id"=>"21739912000"}, {"first_name"=>"Thomas", "last_name"=>"Mailund", "scopus_author_id"=>"14619483800"}, {"first_name"=>"Mogens Sandø", "last_name"=>"Lund", "scopus_author_id"=>"24485450300"}, {"first_name"=>"Bernt", "last_name"=>"Guldbrandtsen", "scopus_author_id"=>"6602740929"}], "year"=>2011, "source"=>"PLoS ONE", "identifiers"=>{"scopus"=>"2-s2.0-80355136467", "doi"=>"10.1371/journal.pone.0027061", "pui"=>"362861822", "issn"=>"19326203", "pmid"=>"22073255", "isbn"=>"3412080225", "sgr"=>"80355136467"}, "id"=>"738887a7-89de-3f27-bbbd-bac741108752", "abstract"=>"INTRODUCTION: The state-of-the-art for dealing with multiple levels of relationship among the samples in genome-wide association studies (GWAS) is unified mixed model analysis (MMA). This approach is very flexible, can be applied to both family-based and population-based samples, and can be extended to incorporate other effects in a straightforward and rigorous fashion. Here, we present a complementary approach, called 'GENMIX (genealogy based mixed model)' which combines advantages from two powerful GWAS methods: genealogy-based haplotype grouping and MMA.\\n\\nSUBJECTS AND METHODS: We validated GENMIX using genotyping data of Danish Jersey cattle and simulated phenotype and compared to the MMA. We simulated scenarios for three levels of heritability (0.21, 0.34, and 0.64), seven levels of MAF (0.05, 0.10, 0.15, 0.20, 0.25, 0.35, and 0.45) and five levels of QTL effect (0.1, 0.2, 0.5, 0.7 and 1.0 in phenotypic standard deviation unit). Each of these 105 possible combinations (3 h(2) x 7 MAF x 5 effects) of scenarios was replicated 25 times.\\n\\nRESULTS: GENMIX provides a better ranking of markers close to the causative locus' location. GENMIX outperformed MMA when the QTL effect was small and the MAF at the QTL was low. In scenarios where MAF was high or the QTL affecting the trait had a large effect both GENMIX and MMA performed similarly.\\n\\nCONCLUSION: In discovery studies, where high-ranking markers are identified and later examined in validation studies, we therefore expect GENMIX to enrich candidates brought to follow-up studies with true positives over false positives more than the MMA would.", "link"=>"http://www.mendeley.com/research/local-genealogies-linear-mixed-model-genomewide-association-mapping-complex-pedigreed-populations", "reader_count"=>26, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>4, "Librarian"=>1, "Researcher"=>8, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>6, "Student > Master"=>1, "Student > Bachelor"=>2, "Professor"=>2}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>4, "Librarian"=>1, "Researcher"=>8, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>6, "Student > Master"=>1, "Student > Bachelor"=>2, "Professor"=>2}, "reader_count_by_subject_area"=>{"Unspecified"=>1, "Environmental Science"=>1, "Agricultural and Biological Sciences"=>21, "Arts and Humanities"=>1, "Social Sciences"=>1, "Computer Science"=>1}, "reader_count_by_subdiscipline"=>{"Social Sciences"=>{"Social Sciences"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>21}, "Computer Science"=>{"Computer Science"=>1}, "Unspecified"=>{"Unspecified"=>1}, "Environmental Science"=>{"Environmental Science"=>1}, "Arts and Humanities"=>{"Arts and Humanities"=>1}}, "reader_count_by_country"=>{"Canada"=>1, "Denmark"=>1}, "group_count"=>1}

Scopus | Further Information

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Figshare

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  • {"files"=>["https://ndownloader.figshare.com/files/717331"], "description"=>"<p>Distribution of the highest-ranking marker within a 1 Mbp radius of a quantitative trait nucleotide with MAF = 0.10 for 375 replicates (3 h<sup>2</sup> x 5 QTL effects x 25 replicates).</p>", "links"=>[], "tags"=>["highest-ranking", "mbp", "radius", "quantitative", "nucleotide", "375", "replicates", "qtl", "25"], "article_id"=>387684, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Goutam Sahana", "Thomas Mailund", "Mogens Sandø Lund", "Bernt Guldbrandtsen"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0027061.g002", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Distribution_of_the_highest_ranking_marker_within_a_1_Mbp_radius_of_a_quantitative_trait_nucleotide_with_MAF_0_10_for_375_replicates_3_h_2_x_5_QTL_effects_x_25_replicates_/387684", "title"=>"Distribution of the highest-ranking marker within a 1 Mbp radius of a quantitative trait nucleotide with MAF = 0.10 for 375 replicates (3 h<sup>2</sup> x 5 QTL effects x 25 replicates).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-20 12:06:38"}
  • {"files"=>["https://ndownloader.figshare.com/files/717392"], "description"=>"<p>The QTL effects in phenotypic standard deviation unit are in the X-axis and the power to detect QTL is in the Y-axis. The first row is for MAF of 0.10 and the second row is for MAF of 0.45.</p>", "links"=>[], "tags"=>["qtl", "levels", "heritability", "genmix", "mma"], "article_id"=>387751, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Goutam Sahana", "Thomas Mailund", "Mogens Sandø Lund", "Bernt Guldbrandtsen"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0027061.g003", "stats"=>{"downloads"=>1, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_power_to_detect_QTL_with_different_effect_size_for_three_different_levels_of_heritability_using_GENMIX_9633_and_MMA_9651_/387751", "title"=>"The power to detect QTL with different effect size for three different levels of heritability using GENMIX (□) and MMA (△).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-20 12:06:57"}

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