Joint Modelling of Confounding Factors and Prominent Genetic Regulators Provides Increased Accuracy in Genetical Genomics Studies
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{"title"=>"Joint modelling of confounding factors and prominent genetic regulators provides increased accuracy in genetical genomics studies", "type"=>"journal", "authors"=>[{"first_name"=>"Nicoló", "last_name"=>"Fusi", "scopus_author_id"=>"55026470700"}, {"first_name"=>"Oliver", "last_name"=>"Stegle", "scopus_author_id"=>"57194781099"}, {"first_name"=>"Neil D.", "last_name"=>"Lawrence", "scopus_author_id"=>"9279186200"}], "year"=>2012, "source"=>"PLoS Computational Biology", "identifiers"=>{"sgr"=>"84857467272", "pui"=>"364329949", "isbn"=>"1553-7358", "doi"=>"10.1371/journal.pcbi.1002330", "issn"=>"1553734X", "scopus"=>"2-s2.0-84857467272", "pmid"=>"22241974"}, "id"=>"ff435e28-5235-359c-a4b9-54799cde19fb", "abstract"=>"Expression quantitative trait loci (eQTL) studies are an integral tool to investigate the genetic component of gene expression variation. A major challenge in the analysis of such studies are hidden confounding factors, such as unobserved covariates or unknown subtle environmental perturbations. These factors can induce a pronounced artifactual correlation structure in the expression profiles, which may create spurious false associations or mask real genetic association signals. Here, we report PANAMA (Probabilistic ANAlysis of genoMic dAta), a novel probabilistic model to account for confounding factors within an eQTL analysis. In contrast to previous methods, PANAMA learns hidden factors jointly with the effect of prominent genetic regulators. As a result, this new model can more accurately distinguish true genetic association signals from confounding variation. We applied our model and compared it to existing methods on different datasets and biological systems. PANAMA consistently performs better than alternative methods, and finds in particular substantially more trans regulators. Importantly, our approach not only identifies a greater number of associations, but also yields hits that are biologically more plausible and can be better reproduced between independent studies. A software implementation of PANAMA is freely available online at http://ml.sheffield.ac.uk/qtl/.", "link"=>"http://www.mendeley.com/research/joint-modelling-confounding-factors-prominent-genetic-regulators-provides-increased-accuracy-genetic", "reader_count"=>153, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>12, "Researcher"=>45, "Student > Doctoral Student"=>4, "Student > Ph. D. Student"=>58, "Student > Postgraduate"=>3, "Student > Master"=>16, "Other"=>2, "Student > Bachelor"=>6, "Professor"=>6}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>12, "Researcher"=>45, "Student > Doctoral Student"=>4, "Student > Ph. D. Student"=>58, "Student > Postgraduate"=>3, "Student > Master"=>16, "Other"=>2, "Student > Bachelor"=>6, "Professor"=>6}, "reader_count_by_subject_area"=>{"Unspecified"=>2, "Engineering"=>4, "Biochemistry, Genetics and Molecular Biology"=>13, "Mathematics"=>15, "Agricultural and Biological Sciences"=>87, "Medicine and Dentistry"=>1, "Physics and Astronomy"=>1, "Psychology"=>1, "Chemistry"=>1, "Computer Science"=>28}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>4}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>1}, "Chemistry"=>{"Chemistry"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Psychology"=>{"Psychology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>87}, "Computer Science"=>{"Computer Science"=>28}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>13}, "Mathematics"=>{"Mathematics"=>15}, "Unspecified"=>{"Unspecified"=>2}}, "reader_count_by_country"=>{"Austria"=>1, "Korea (South)"=>1, "Belgium"=>1, "United States"=>11, "Norway"=>1, "Luxembourg"=>1, "United Kingdom"=>2, "Germany"=>2}, "group_count"=>6}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/695013"], "description"=>"<p>(<b>a</b>) Representation of the linear model used by PANAMA to correct for the effect of confounding factors. (<b>b</b>) Alternative settings of confounders in relation to true genetic signals: First, orthogonality between confounders and genetics. The variation in the gene expression levels (green arrow) can be better explained by the SNP (blue arrow). Second, statistical overlap between variation explained by confounders and the genetic variation as often found in <i>trans</i> hotspots. Gene expression variation can be equally well explained as genetic or due to a confounding factor. Previous methods focus in the first setting, while PANAMA is able to handle both situations. (<b>c</b>) PANAMA applied to the yeast eQTL dataset. Pronounced <i>trans</i> regulators that overlap with the learnt confounding factors are highlighted in red.</p>", "links"=>[], "tags"=>["panama"], "article_id"=>365437, "categories"=>["Mathematics", "Genetics"], "users"=>["Nicoló Fusi", "Oliver Stegle", "Neil D. Lawrence"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002330.g001", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Illustration_of_the_PANAMA_model_/365437", "title"=>"Illustration of the PANAMA model.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-01-05 01:30:37"}
  • {"files"=>["https://ndownloader.figshare.com/files/695119"], "description"=>"<p>(<b>a,b</b>) number of recovered <i>cis</i> and <i>trans</i> associations as a function of the chosen false discovery rate cutoff. To circumvent biases due to linkage, at most one association per chromosome and gene is counted. (<b>c</b>) Receiver Operating Characteristics (ROC) for recovering true simulated associations, depicting the true positive rate (TPR) as a function of the permitted false positive rate (FPR). (<b>d</b>) inflation factors, defined as , indicating either inflated p-value distributions () or deflation () of the respective tests statistics. (<b>e</b>) Area under the ROC curve for alternative simulated datasets, subsampling certain fractions of number of simulated <i>trans</i> association. (<b>f</b>) Area under the ROC curve for alternative simulated datasets, subsampling the number of simulated confounding factors.</p>", "links"=>[], "tags"=>["panama", "methods", "simulated", "eqtl"], "article_id"=>365540, "categories"=>["Mathematics", "Genetics"], "users"=>["Nicoló Fusi", "Oliver Stegle", "Neil D. Lawrence"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002330.g002", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Evaluation_of_PANAMA_and_alternative_methods_on_the_simulated_eQTL_dataset_/365540", "title"=>"Evaluation of PANAMA and alternative methods on the simulated eQTL dataset.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-01-05 01:32:20"}
  • {"files"=>["https://ndownloader.figshare.com/files/353859", "https://ndownloader.figshare.com/files/353910", "https://ndownloader.figshare.com/files/353936", "https://ndownloader.figshare.com/files/353980", "https://ndownloader.figshare.com/files/354015", "https://ndownloader.figshare.com/files/354067", "https://ndownloader.figshare.com/files/354108", "https://ndownloader.figshare.com/files/354157", "https://ndownloader.figshare.com/files/354208", "https://ndownloader.figshare.com/files/354264", "https://ndownloader.figshare.com/files/354331", "https://ndownloader.figshare.com/files/354385", "https://ndownloader.figshare.com/files/354476", "https://ndownloader.figshare.com/files/354538"], "description"=>"<div><p>Expression quantitative trait loci (eQTL) studies are an integral tool to investigate the genetic component of gene expression variation. A major challenge in the analysis of such studies are hidden confounding factors, such as unobserved covariates or unknown subtle environmental perturbations. These factors can induce a pronounced artifactual correlation structure in the expression profiles, which may create spurious false associations or mask real genetic association signals. Here, we report PANAMA (Probabilistic ANAlysis of genoMic dAta), a novel probabilistic model to account for confounding factors within an eQTL analysis. In contrast to previous methods, PANAMA learns hidden factors jointly with the effect of prominent genetic regulators. As a result, this new model can more accurately distinguish true genetic association signals from confounding variation. We applied our model and compared it to existing methods on different datasets and biological systems. PANAMA consistently performs better than alternative methods, and finds in particular substantially more <em>trans</em> regulators. Importantly, our approach not only identifies a greater number of associations, but also yields hits that are biologically more plausible and can be better reproduced between independent studies. A software implementation of PANAMA is freely available online at <a href=\"http://ml.sheffield.ac.uk/qtl/\">http://ml.sheffield.ac.uk/qtl/</a>.</p> </div>", "links"=>[], "tags"=>["confounding", "factors", "regulators", "provides", "genetical", "genomics", "studies"], "article_id"=>129932, "categories"=>["Mathematics", "Genetics"], "users"=>["Nicoló Fusi", "Oliver Stegle", "Neil D. Lawrence"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1002330.s001", "https://dx.doi.org/10.1371/journal.pcbi.1002330.s002", "https://dx.doi.org/10.1371/journal.pcbi.1002330.s003", "https://dx.doi.org/10.1371/journal.pcbi.1002330.s004", "https://dx.doi.org/10.1371/journal.pcbi.1002330.s005", "https://dx.doi.org/10.1371/journal.pcbi.1002330.s006", "https://dx.doi.org/10.1371/journal.pcbi.1002330.s007", "https://dx.doi.org/10.1371/journal.pcbi.1002330.s008", "https://dx.doi.org/10.1371/journal.pcbi.1002330.s009", "https://dx.doi.org/10.1371/journal.pcbi.1002330.s010", "https://dx.doi.org/10.1371/journal.pcbi.1002330.s011", "https://dx.doi.org/10.1371/journal.pcbi.1002330.s012", "https://dx.doi.org/10.1371/journal.pcbi.1002330.s013", "https://dx.doi.org/10.1371/journal.pcbi.1002330.s014"], "stats"=>{"downloads"=>77, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Joint_Modelling_of_Confounding_Factors_and_Prominent_Genetic_Regulators_Provides_Increased_Accuracy_in_Genetical_Genomics_Studies/129932", "title"=>"Joint Modelling of Confounding Factors and Prominent Genetic Regulators Provides Increased Accuracy in Genetical Genomics Studies", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2012-01-05 02:45:32"}
  • {"files"=>["https://ndownloader.figshare.com/files/695186"], "description"=>"<p>(<b>a,b</b>): number of <i>cis</i> and <i>trans</i> associations found by alternative methods as a function of the chosen FDR cutoff. (<b>c</b>) Inflation factors of alternative methods, defined as . (<b>d</b>) Consistency of calling <i>cis</i> associations between two independent glucose yeast eQTL datasets. (<b>e</b>) Consistency of calling eQTL hotspots between two independent glucose yeast datasets, where SNPs are ordered by the extent of <i>trans</i> regulation as determined by .</p>", "links"=>[], "tags"=>["methods", "eqtl", "dataset", "segregating", "yeast", "strains"], "article_id"=>365607, "categories"=>["Mathematics", "Genetics"], "users"=>["Nicoló Fusi", "Oliver Stegle", "Neil D. Lawrence"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002330.g003", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Evaluation_of_alternative_methods_on_the_eQTL_dataset_from_segregating_yeast_strains_glucose_condition_/365607", "title"=>"Evaluation of alternative methods on the eQTL dataset from segregating yeast strains (glucose condition).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-01-05 01:33:27"}

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Relative Metric

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