From SNPs to Genes: Disease Association at the Gene Level
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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/382595", "https://ndownloader.figshare.com/files/384647", "https://ndownloader.figshare.com/files/384845", "https://ndownloader.figshare.com/files/384916", "https://ndownloader.figshare.com/files/388902", "https://ndownloader.figshare.com/files/389075", "https://ndownloader.figshare.com/files/389277", "https://ndownloader.figshare.com/files/389317", "https://ndownloader.figshare.com/files/389337", "https://ndownloader.figshare.com/files/389365"], "description"=>"<div><p>Interpreting Genome-Wide Association Studies (GWAS) at a gene level is an important step towards understanding the molecular processes that lead to disease. In order to incorporate prior biological knowledge such as pathways and protein interactions in the analysis of GWAS data it is necessary to derive one measure of association for each gene. We compare three different methods to obtain gene-wide test statistics from Single Nucleotide Polymorphism (SNP) based association data: choosing the test statistic from the most significant SNP; the mean test statistics of all SNPs; and the mean of the top quartile of all test statistics. We demonstrate that the gene-wide test statistics can be controlled for the number of SNPs within each gene and show that all three methods perform considerably better than expected by chance at identifying genes with confirmed associations. By applying each method to GWAS data for Crohn's Disease and Type 1 Diabetes we identified new potential disease genes.</p> </div>", "links"=>[], "tags"=>["snps"], "article_id"=>135579, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Benjamin Lehne", "Cathryn M. Lewis", "Thomas Schlitt"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0020133.s001", "https://dx.doi.org/10.1371/journal.pone.0020133.s002", "https://dx.doi.org/10.1371/journal.pone.0020133.s003", "https://dx.doi.org/10.1371/journal.pone.0020133.s004", "https://dx.doi.org/10.1371/journal.pone.0020133.s005", "https://dx.doi.org/10.1371/journal.pone.0020133.s006", "https://dx.doi.org/10.1371/journal.pone.0020133.s007", "https://dx.doi.org/10.1371/journal.pone.0020133.s008", "https://dx.doi.org/10.1371/journal.pone.0020133.s009", "https://dx.doi.org/10.1371/journal.pone.0020133.s010"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/From_SNPs_to_Genes_Disease_Association_at_the_Gene_Level/135579", "title"=>"From SNPs to Genes: Disease Association at the Gene Level", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2011-06-30 01:32:59"}
  • {"files"=>["https://ndownloader.figshare.com/files/759481"], "description"=>"<p>We assigned SNPs on the Affymetrix 500K genotyping array to protein-coding genes. SNPs were assigned to a gene if they are located within the transcribed region or within a 40 kilobase flanking window around the transcribed region. Where flanking windows overlapped SNPs were assigned to their closest gene only.</p>", "links"=>[], "tags"=>["snps", "assigned"], "article_id"=>429861, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Benjamin Lehne", "Cathryn M. Lewis", "Thomas Schlitt"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0020133.g001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Distribution_of_the_number_of_SNPs_assigned_to_genes_/429861", "title"=>"Distribution of the number of SNPs assigned to genes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-06-30 02:44:21"}
  • {"files"=>["https://ndownloader.figshare.com/files/759604"], "description"=>"<p>Multiple test statistics are combined for each gene using three different methods (maxT, meanT, topQ). For each method, the gene-wide test statistic is correlated with the number of SNPs per gene. For these histograms, genes are binned according to their gene-wide test statistic (left axis). The red dots show the mean number of SNPs per gene for every bin (right axis).</p>", "links"=>[], "tags"=>["snps"], "article_id"=>429985, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Benjamin Lehne", "Cathryn M. Lewis", "Thomas Schlitt"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0020133.g002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Confounding_effect_of_the_number_of_SNPs_per_gene_Crohn_s_Disease_/429985", "title"=>"Confounding effect of the number of SNPs per gene (Crohn's Disease).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-06-30 02:46:25"}
  • {"files"=>["https://ndownloader.figshare.com/files/759734"], "description"=>"<p>Genes were assigned to 50 bins according to their p<sub>emp</sub>. Histogram shows the number of genes with <i>p<sub>emp</sub></i> values (left axis). The red line shows the mean number of SNPs per gene for every bin (right axis). In contrast to the gene-wide test statistics we observe no correlation of the number of SNPs per gene with <i>p<sub>emp</sub></i> for any method. We observe an increase of genes with very low <i>p<sub>emp</sub></i> values caused by the actual association signal.</p>", "links"=>[], "tags"=>["empirical", "p-value", "permutations"], "article_id"=>430109, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Benjamin Lehne", "Cathryn M. Lewis", "Thomas Schlitt"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0020133.g003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Distribution_of_empirical_p_value_p_emp_for_Crohn_s_Disease_from_500_000_permutations_of_the_disease_labels_/430109", "title"=>"Distribution of empirical p-value (<i>p<sub>emp</sub></i>) for Crohn's Disease from 500,000 permutations of the disease labels.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-06-30 00:01:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/759885"], "description"=>"<p>For each gene the <i>p<sub>emp</sub></i> is plotted against the uncontrolled p-value (based on the gene-wide test statistic). Each point represents a gene and is coloured according to the number of SNPs assigned to a gene (<i>n</i>). Genes with few SNPs have <i>p<sub>emp</sub></i> values similar to the uncontrolled p-value and therefore cluster along the diagonal. For genes with higher number of SNPs the distribution depends on the method to combine test statistics.</p>", "links"=>[], "tags"=>["p-values", "uncontrolled"], "article_id"=>430263, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Benjamin Lehne", "Cathryn M. Lewis", "Thomas Schlitt"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0020133.g004"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Empirical_p_values_vs_uncontrolled_p_values_Crohn_s_Disease_/430263", "title"=>"Empirical p-values vs. uncontrolled p-values (Crohn's Disease).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-06-30 00:04:23"}
  • {"files"=>["https://ndownloader.figshare.com/files/759987"], "description"=>"<p>To assess the performance of different methods to combine test statistics we plot the proportion of confirmed disease genes (True Positive Rate) against their rank within the whole set of genes (False Positive Rate).</p>", "links"=>[], "tags"=>["curves"], "article_id"=>430364, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Benjamin Lehne", "Cathryn M. Lewis", "Thomas Schlitt"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0020133.g005"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Receiver_Operating_Characteristic_ROC_curves_for_Crohn_s_Disease_CD_and_Type_1_Diabetes_T1D_/430364", "title"=>"Receiver Operating Characteristic (ROC) curves for Crohn's Disease (CD) and Type 1 Diabetes (T1D).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-06-30 00:06:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/760081"], "description"=>"<p>Genes are ordered by chromosome and genomic position; n denominates the number of SNPs per gene. The last three columns show the corresponding ranks for the three methods. <i>italics</i>: genes that are within the true positive list.</p>", "links"=>[], "tags"=>["30", "ranked", "genes", "maxt"], "article_id"=>430454, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Benjamin Lehne", "Cathryn M. Lewis", "Thomas Schlitt"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0020133.t003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_top_30_ranked_genes_for_Crohn_s_Disease_CD_using_the_maxT_method_/430454", "title"=>"The top 30 ranked genes for Crohn's Disease (CD) using the maxT method.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-06-30 00:07:34"}
  • {"files"=>["https://ndownloader.figshare.com/files/760113"], "description"=>"<p>Replicated Disease Genes for Crohn's Disease from <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0020133#pone.0020133-Franke1\" target=\"_blank\">[17]</a> and their ranks for each method.</p>", "links"=>[], "tags"=>["genes", "ranks"], "article_id"=>430491, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Benjamin Lehne", "Cathryn M. Lewis", "Thomas Schlitt"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0020133.t002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Replicated_Disease_Genes_for_Crohn_s_Disease_from_17_and_their_ranks_for_each_method_/430491", "title"=>"Replicated Disease Genes for Crohn's Disease from [17] and their ranks for each method.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-06-30 00:08:11"}
  • {"files"=>["https://ndownloader.figshare.com/files/760149"], "description"=>"<p>Overview statistics of the analysed GWAS datasets and the gene to SNP assignment for Crohn's Disease (CD) and Type 1 Diabetes (T1D).</p>", "links"=>[], "tags"=>["analysed", "GWAS", "datasets", "snp"], "article_id"=>430524, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Benjamin Lehne", "Cathryn M. Lewis", "Thomas Schlitt"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0020133.t001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Overview_statistics_of_the_analysed_GWAS_datasets_and_the_gene_to_SNP_assignment_for_Crohn_s_Disease_CD_and_Type_1_Diabetes_T1D_/430524", "title"=>"Overview statistics of the analysed GWAS datasets and the gene to SNP assignment for Crohn's Disease (CD) and Type 1 Diabetes (T1D).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-06-30 00:08:44"}

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Relative Metric

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