Candidate Causal Regulatory Effects by Integration of Expression QTLs with Complex Trait Genetic Associations
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{"title"=>"Candidate causal regulatory effects by integration of expression QTLs with complex trait genetic associations", "type"=>"journal", "authors"=>[{"first_name"=>"Alexandra C.", "last_name"=>"Nica", "scopus_author_id"=>"57189985825"}, {"first_name"=>"Stephen B.", "last_name"=>"Montgomery", "scopus_author_id"=>"8708455800"}, {"first_name"=>"Antigone S.", "last_name"=>"Dimas", "scopus_author_id"=>"16506100400"}, {"first_name"=>"Barbara E.", "last_name"=>"Stranger", "scopus_author_id"=>"6507901873"}, {"first_name"=>"Claude", "last_name"=>"Beazley", "scopus_author_id"=>"23569388000"}, {"first_name"=>"Inês", "last_name"=>"Barroso", "scopus_author_id"=>"55400421600"}, {"first_name"=>"Emmanouil T.", "last_name"=>"Dermitzakis", "scopus_author_id"=>"35354477100"}], "year"=>2010, "source"=>"PLoS Genetics", "identifiers"=>{"issn"=>"15537390", "scopus"=>"2-s2.0-77952367694", "pui"=>"358837606", "doi"=>"10.1371/journal.pgen.1000895", "isbn"=>"1553-7404 (Electronic)\\n1553-7390 (Linking)", "sgr"=>"77952367694", "pmid"=>"20369022"}, "id"=>"22cab9fe-a510-3679-861d-ade1def542a3", "abstract"=>"The recent success of genome-wide association studies (GWAS) is now followed by the challenge to determine how the reported susceptibility variants mediate complex traits and diseases. Expression quantitative trait loci (eQTLs) have been implicated in disease associations through overlaps between eQTLs and GWAS signals. However, the abundance of eQTLs and the strong correlation structure (LD) in the genome make it likely that some of these overlaps are coincidental and not driven by the same functional variants. In the present study, we propose an empirical methodology, which we call Regulatory Trait Concordance (RTC) that accounts for local LD structure and integrates eQTLs and GWAS results in order to reveal the subset of association signals that are due to cis eQTLs. We simulate genomic regions of various LD patterns with both a single or two causal variants and show that our score outperforms SNP correlation metrics, be they statistical (r(2)) or historical (D'). Following the observation of a significant abundance of regulatory signals among currently published GWAS loci, we apply our method with the goal to prioritize relevant genes for each of the respective complex traits. We detect several potential disease-causing regulatory effects, with a strong enrichment for immunity-related conditions, consistent with the nature of the cell line tested (LCLs). Furthermore, we present an extension of the method in trans, where interrogating the whole genome for downstream effects of the disease variant can be informative regarding its unknown primary biological effect. We conclude that integrating cellular phenotype associations with organismal complex traits will facilitate the biological interpretation of the genetic effects on these traits.", "link"=>"http://www.mendeley.com/research/candidate-causal-regulatory-effects-integration-expression-qtls-complex-trait-genetic-associations", "reader_count"=>294, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>23, "Researcher"=>92, "Student > Doctoral Student"=>6, "Student > Ph. D. Student"=>102, "Student > Postgraduate"=>10, "Student > Master"=>24, "Other"=>11, "Student > Bachelor"=>9, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>1, "Professor"=>13}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>23, "Researcher"=>92, "Student > Doctoral Student"=>6, "Student > Ph. D. Student"=>102, "Student > Postgraduate"=>10, "Student > Master"=>24, "Other"=>11, "Student > Bachelor"=>9, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>1, "Professor"=>13}, "reader_count_by_subject_area"=>{"Unspecified"=>8, "Agricultural and Biological Sciences"=>183, "Business, Management and Accounting"=>1, "Veterinary Science and Veterinary Medicine"=>1, "Computer Science"=>21, "Engineering"=>2, "Biochemistry, Genetics and Molecular Biology"=>39, "Mathematics"=>12, "Medicine and Dentistry"=>21, "Neuroscience"=>3, "Pharmacology, Toxicology and Pharmaceutical Science"=>1, "Physics and Astronomy"=>1, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>21}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Mathematics"=>{"Mathematics"=>12}, "Unspecified"=>{"Unspecified"=>8}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>1}, "Engineering"=>{"Engineering"=>2}, "Neuroscience"=>{"Neuroscience"=>3}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>183}, "Computer Science"=>{"Computer Science"=>21}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>39}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>1}}, "reader_count_by_country"=>{"Romania"=>1, "Hungary"=>1, "United States"=>28, "United Kingdom"=>3, "Spain"=>1, "New Zealand"=>1, "Sweden"=>1, "Austria"=>1, "Norway"=>2, "Denmark"=>1, "Brazil"=>1, "Italy"=>3, "France"=>1, "Germany"=>3}, "group_count"=>10}

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  • {"files"=>["https://ndownloader.figshare.com/files/425393", "https://ndownloader.figshare.com/files/425403"], "description"=>"<div><p>The recent success of genome-wide association studies (GWAS) is now followed by the challenge to determine how the reported susceptibility variants mediate complex traits and diseases. Expression quantitative trait loci (eQTLs) have been implicated in disease associations through overlaps between eQTLs and GWAS signals. However, the abundance of eQTLs and the strong correlation structure (LD) in the genome make it likely that some of these overlaps are coincidental and not driven by the same functional variants. In the present study, we propose an empirical methodology, which we call Regulatory Trait Concordance (RTC) that accounts for local LD structure and integrates eQTLs and GWAS results in order to reveal the subset of association signals that are due to <em>cis</em> eQTLs. We simulate genomic regions of various LD patterns with both a single or two causal variants and show that our score outperforms SNP correlation metrics, be they statistical (r<sup>2</sup>) or historical (D'). Following the observation of a significant abundance of regulatory signals among currently published GWAS loci, we apply our method with the goal to prioritize relevant genes for each of the respective complex traits. We detect several potential disease-causing regulatory effects, with a strong enrichment for immunity-related conditions, consistent with the nature of the cell line tested (LCLs). Furthermore, we present an extension of the method in <em>trans</em>, where interrogating the whole genome for downstream effects of the disease variant can be informative regarding its unknown primary biological effect. We conclude that integrating cellular phenotype associations with organismal complex traits will facilitate the biological interpretation of the genetic effects on these traits.</p></div>", "links"=>[], "tags"=>["causal", "effects", "qtls", "associations"], "article_id"=>143977, "categories"=>["Genetics"], "users"=>["Alexandra C. Nica", "Stephen B. Montgomery", "Antigone S. Dimas", "Barbara E. Stranger", "Claude Beazley", "Inês Barroso", "Emmanouil T. Dermitzakis"], "doi"=>["https://dx.doi.org/10.1371/journal.pgen.1000895.s001", "https://dx.doi.org/10.1371/journal.pgen.1000895.s002"], "stats"=>{"downloads"=>3, "page_views"=>37, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Candidate_Causal_Regulatory_Effects_by_Integration_of_Expression_QTLs_with_Complex_Trait_Genetic_Associations/143977", "title"=>"Candidate Causal Regulatory Effects by Integration of Expression QTLs with Complex Trait Genetic Associations", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2010-04-01 01:06:17"}
  • {"files"=>["https://ndownloader.figshare.com/files/855795"], "description"=>"<p>Distribution of best RTC Scores per GWAS SNP stratified by immunity relatedness. Histogram contains results from the analysis of 130 hotspot intervals with colocalizing disease SNPs and <i>cis</i> eQTLs. We observe a significant overrepresentation of high-scoring (RTC > = 0.9) candidate genes (black bars) for immunity related complex traits compared to non-immunity related ones (grey bars) (Fisher's Exact Test, P-value = 0.0125).</p>", "links"=>[], "tags"=>["immunity-related", "high-scoring"], "article_id"=>526248, "categories"=>["Genetics"], "users"=>["Alexandra C. Nica", "Stephen B. Montgomery", "Antigone S. Dimas", "Barbara E. Stranger", "Claude Beazley", "Inês Barroso", "Emmanouil T. Dermitzakis"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1000895.g007", "stats"=>{"downloads"=>0, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Overrepresentation_of_immunity_related_high_scoring_cis_signals_/526248", "title"=>"Overrepresentation of immunity-related high-scoring <i>cis</i> signals.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-04-01 01:44:08"}
  • {"files"=>["https://ndownloader.figshare.com/files/855983"], "description"=>"<p>Candidate <i>trans</i> genes likely involved in the same biological pathways, relevant to the GWAS SNPs. Signals relating to the same hotspot interval separated by a horizontal line. Table contains only the confident results (RTC Score > = 0.9) for the 6 immunity related intervals.</p>", "links"=>[], "tags"=>["genetics and genomics/complex traits", "genetics and genomics/gene expression", "genetics and genomics/genetics of disease"], "article_id"=>526435, "categories"=>["Genetics"], "users"=>["Alexandra C. Nica", "Stephen B. Montgomery", "Antigone S. Dimas", "Barbara E. Stranger", "Claude Beazley", "Inês Barroso", "Emmanouil T. Dermitzakis"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1000895.t002", "stats"=>{"downloads"=>18, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Candidate_trans_results_/526435", "title"=>"Candidate <i>trans</i> results.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2010-04-01 01:47:15"}
  • {"files"=>["https://ndownloader.figshare.com/files/855927"], "description"=>"<p>We contrast the LR adjusted R<sup>2</sup> at the eQTL after and before correction of the dSNP and observe that while most high scoring pairs correspond to cases of lowest variance left unexplained, other interesting cases would be missed solely by using an arbitrary variance threshold.</p>", "links"=>[], "tags"=>["eqtl", "variance", "explained", "dsnp", "rtc"], "article_id"=>526370, "categories"=>["Genetics"], "users"=>["Alexandra C. Nica", "Stephen B. Montgomery", "Antigone S. Dimas", "Barbara E. Stranger", "Claude Beazley", "Inês Barroso", "Emmanouil T. Dermitzakis"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1000895.g009", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_fraction_of_eQTL_variance_explained_away_by_the_dSNP_versus_the_RTC_score_/526370", "title"=>"The fraction of eQTL variance explained away by the dSNP versus the RTC score.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-04-01 01:46:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/855674"], "description"=>"<p>Simulation results depicting the relationship between the RTC score and the D' (eQTL, dSNP) when they tag different causal SNPs (H<sub>0</sub>: left panel) versus one causal SNP (H<sub>1</sub>: right panel). D' is not correlated with RTC, therefore it will not determine high scores on its own in the absence of a common functional variant. Under the H<sub>1</sub>, the majority of high RTC scoring pairs have high D', but in the case of a perfect historical correlation scenario, it's impossible to distinguish causal from coincidental effects with D' only.</p>", "links"=>[], "tags"=>["properties", "varying"], "article_id"=>526128, "categories"=>["Genetics"], "users"=>["Alexandra C. Nica", "Stephen B. Montgomery", "Antigone S. Dimas", "Barbara E. Stranger", "Claude Beazley", "Inês Barroso", "Emmanouil T. Dermitzakis"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1000895.g005", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_RTC_score_properties_when_varying_D_/526128", "title"=>"RTC score properties when varying D'.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-04-01 01:42:08"}
  • {"files"=>["https://ndownloader.figshare.com/files/856022"], "description"=>"<p>Candidate genes (RTC Score > = 0.9) for <i>cis</i> regulatory mediated GWAS effects. The higher the score, the more likely it is that the GWAS SNP and the eQTL for the gene shown are tagging the same functional variant.</p>", "links"=>[], "tags"=>["genetics and genomics/complex traits", "genetics and genomics/gene expression", "genetics and genomics/genetics of disease"], "article_id"=>526472, "categories"=>["Genetics"], "users"=>["Alexandra C. Nica", "Stephen B. Montgomery", "Antigone S. Dimas", "Barbara E. Stranger", "Claude Beazley", "Inês Barroso", "Emmanouil T. Dermitzakis"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1000895.t001", "stats"=>{"downloads"=>9, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Candidate_cis_results_/526472", "title"=>"Candidate <i>cis</i> results.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2010-04-01 01:47:52"}
  • {"files"=>["https://ndownloader.figshare.com/files/855527"], "description"=>"<p>The RTC score is uniformly distributed for simulated eQTLs and dSNPs tagging two different causal variants in the same interval (left panel). The RTC Score is right-skewed for simulated eQTLs and dSNPs tagging the same functional variant (middle panel). The RTC score is sensitive to associations tagging a common functional variant in non-simulated data, when the GWAS trait is gene expression (GenCord LCL samples – right panel).</p>", "links"=>[], "tags"=>["genetics and genomics/complex traits", "genetics and genomics/gene expression", "genetics and genomics/genetics of disease"], "article_id"=>525980, "categories"=>["Genetics"], "users"=>["Alexandra C. Nica", "Stephen B. Montgomery", "Antigone S. Dimas", "Barbara E. Stranger", "Claude Beazley", "Inês Barroso", "Emmanouil T. Dermitzakis"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1000895.g003", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_RTC_score_distribution_/525980", "title"=>"RTC score distribution.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-04-01 01:39:40"}
  • {"files"=>["https://ndownloader.figshare.com/files/855399"], "description"=>"<p>QQ plot depicting the excess of significant regulatory signal in GWAS data (976 NHGRI SNPs). For both the <i>cis</i> and <i>trans</i> analyses, the −log<sub>10</sub>(P-value) of the best associations per SNP are plotted. In red, the distribution of these values for GWAS SNPs is compared to that of the median of 1,000 sets of 976 random SNPs with same MAF distribution. In black, the estimated upper limit of the 95% confidence interval is plotted.</p>", "links"=>[], "tags"=>["variants", "GWAS"], "article_id"=>525849, "categories"=>["Genetics"], "users"=>["Alexandra C. Nica", "Stephen B. Montgomery", "Antigone S. Dimas", "Barbara E. Stranger", "Claude Beazley", "Inês Barroso", "Emmanouil T. Dermitzakis"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1000895.g001", "stats"=>{"downloads"=>0, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Excess_of_regulatory_variants_among_GWAS_signals_/525849", "title"=>"Excess of regulatory variants among GWAS signals.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-04-01 01:37:29"}
  • {"files"=>["https://ndownloader.figshare.com/files/855623"], "description"=>"<p>Simulation results depicting the relationship between the RTC score and the r<sup>2</sup> (eQTL, dSNP) when they tag different causal SNPs (H<sub>0</sub>: left panel) versus one causal SNP (H<sub>1</sub>: right panel). The RTC increases as expected with increased r<sup>2</sup> between the eQTL and the dSNP, but when tagging the same functional variant, various lower pairwise r<sup>2</sup> combinations can determine a high RTC. This makes r<sup>2</sup> on its own insufficient to detect shared causal effects.</p>", "links"=>[], "tags"=>["rtc", "varying"], "article_id"=>526079, "categories"=>["Genetics"], "users"=>["Alexandra C. Nica", "Stephen B. Montgomery", "Antigone S. Dimas", "Barbara E. Stranger", "Claude Beazley", "Inês Barroso", "Emmanouil T. Dermitzakis"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1000895.g004", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Properties_of_the_RTC_score_when_varying_r_2_/526079", "title"=>"Properties of the RTC score when varying r<sup>2</sup>.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-04-01 01:41:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/855854"], "description"=>"<p>Neither r<sup>2</sup> nor D' between the eQTL and the GWAS SNP are direct predictors of a high RTC Score. Highlighted here are the results from the <i>cis</i> and <i>trans</i> analyses. We obtain high scoring results (RTC Scores > = 0.8 in blue) for cases with a high correlation between the disease SNP and the eQTL as expected, but also for pairs with low statistical correlation (r<sup>2</sup> – top panel). As shown in the bottom panel, many of these high scoring pairs are historically correlated (D' = 1), but so are many more by chance. Additionally, we can detect high scoring pairs with low D' as well. Hence, no obvious combination of the two LD measures can predict a high RTC Score.</p>", "links"=>[], "tags"=>["rtc", "compared", "ld", "observed"], "article_id"=>526308, "categories"=>["Genetics"], "users"=>["Alexandra C. Nica", "Stephen B. Montgomery", "Antigone S. Dimas", "Barbara E. Stranger", "Claude Beazley", "Inês Barroso", "Emmanouil T. Dermitzakis"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1000895.g008", "stats"=>{"downloads"=>1, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_RTC_method_compared_to_standard_LD_measurements_in_the_observed_data_/526308", "title"=>"The RTC method compared to standard LD measurements in the observed data.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-04-01 01:45:08"}
  • {"files"=>["https://ndownloader.figshare.com/files/855467"], "description"=>"<p>The −log10(P-value) of the best associations per GWAS SNPs and a set of random SNPs are plotted. As expected given the tissue (LCLs), immunity related phenotypes are mainly responsible for the enrichment.</p>", "links"=>[], "tags"=>["enrichment", "stratified", "immunity"], "article_id"=>525921, "categories"=>["Genetics"], "users"=>["Alexandra C. Nica", "Stephen B. Montgomery", "Antigone S. Dimas", "Barbara E. Stranger", "Claude Beazley", "Inês Barroso", "Emmanouil T. Dermitzakis"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1000895.g002", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Cis_regulatory_enrichment_stratified_by_immunity_relatedness_/525921", "title"=>"<i>Cis</i> regulatory enrichment stratified by immunity relatedness.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-04-01 01:38:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/855734"], "description"=>"<p>Simulation results depicting the relationship between the RTC score and the local LD structure (median r<sup>2</sup>) under the null (different causal SNPs - left panel) and alternative hypothesis (same causal SNP - right panel). Under H<sub>0</sub>, the RTC score is evenly distributed, therefore intervals with overall low LD will not determine high RTC scores. Under H<sub>1</sub>, the RTC performs best in intervals with overall low LD, where the correlation between the eQTL and other non-disease SNPs decays much faster, making the dSNP correction stand out.</p>", "links"=>[], "tags"=>["properties", "varying", "median", "hotspot"], "article_id"=>526185, "categories"=>["Genetics"], "users"=>["Alexandra C. Nica", "Stephen B. Montgomery", "Antigone S. Dimas", "Barbara E. Stranger", "Claude Beazley", "Inês Barroso", "Emmanouil T. Dermitzakis"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1000895.g006", "stats"=>{"downloads"=>1, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_RTC_score_properties_when_varying_the_median_r_2_of_the_hotspot_interval_/526185", "title"=>"RTC score properties when varying the median r<sup>2</sup> of the hotspot interval.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-04-01 01:43:05"}

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  • {"unique-ip"=>"13", "full-text"=>"11", "pdf"=>"6", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"10"}
  • {"unique-ip"=>"17", "full-text"=>"15", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"5", "year"=>"2015", "month"=>"11"}
  • {"unique-ip"=>"14", "full-text"=>"13", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"12"}
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  • {"unique-ip"=>"9", "full-text"=>"7", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"8", "cited-by"=>"0", "year"=>"2016", "month"=>"2"}
  • {"unique-ip"=>"10", "full-text"=>"12", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"3"}
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  • {"unique-ip"=>"15", "full-text"=>"15", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"9"}
  • {"unique-ip"=>"8", "full-text"=>"6", "pdf"=>"8", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"10"}
  • {"unique-ip"=>"6", "full-text"=>"7", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"11"}
  • {"unique-ip"=>"10", "full-text"=>"10", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"12"}
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  • {"unique-ip"=>"13", "full-text"=>"16", "pdf"=>"9", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2017", "month"=>"7"}
  • {"unique-ip"=>"14", "full-text"=>"12", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2017", "month"=>"8"}
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  • {"unique-ip"=>"14", "full-text"=>"13", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2017", "month"=>"10"}
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  • {"unique-ip"=>"13", "full-text"=>"12", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"12"}
  • {"unique-ip"=>"10", "full-text"=>"6", "pdf"=>"7", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"1"}
  • {"unique-ip"=>"13", "full-text"=>"10", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"3"}
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  • {"unique-ip"=>"13", "full-text"=>"13", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"5"}
  • {"unique-ip"=>"11", "full-text"=>"10", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"6"}
  • {"unique-ip"=>"16", "full-text"=>"14", "pdf"=>"6", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"7"}
  • {"unique-ip"=>"9", "full-text"=>"11", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2018", "month"=>"8"}
  • {"unique-ip"=>"13", "full-text"=>"13", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"10"}
  • {"unique-ip"=>"8", "full-text"=>"8", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"9"}
  • {"unique-ip"=>"16", "full-text"=>"18", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"11"}
  • {"unique-ip"=>"11", "full-text"=>"13", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"12"}
  • {"unique-ip"=>"14", "full-text"=>"8", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"2"}
  • {"unique-ip"=>"15", "full-text"=>"22", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"3"}
  • {"unique-ip"=>"21", "full-text"=>"19", "pdf"=>"7", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2019", "month"=>"4"}
  • {"unique-ip"=>"16", "full-text"=>"22", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"7", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"5"}

Relative Metric

{"start_date"=>"2010-01-01T00:00:00Z", "end_date"=>"2010-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences", "average_usage"=>[288, 576, 733, 867, 984, 1087, 1182, 1267, 1346, 1424, 1501, 1577, 1646, 1711, 1778, 1841, 1908, 1970, 2034, 2102, 2162, 2227, 2296, 2359, 2422, 2482, 2550, 2610, 2679, 2747, 2820, 2887, 2955, 3009, 3067, 3130, 3200, 3257, 3322, 3379, 3443, 3507, 3571, 3632, 3683, 3753, 3822, 3877]}, {"subject_area"=>"/Biology and life sciences/Cell biology", "average_usage"=>[280, 562, 725, 863, 974, 1083, 1177, 1268, 1347, 1421, 1489, 1570, 1638, 1706, 1763, 1823, 1890, 1951, 2016, 2076, 2134, 2192, 2257, 2319, 2378, 2438, 2501, 2572, 2634, 2700, 2759, 2825, 2887, 2936, 3007, 3070, 3121, 3184, 3237, 3304, 3363, 3425, 3484, 3531, 3612, 3663, 3718, 3771]}, {"subject_area"=>"/Biology and life sciences/Genetics", "average_usage"=>[306, 610, 768, 915, 1043, 1164, 1255, 1349, 1432, 1511, 1592, 1674, 1744, 1817, 1889, 1950, 2028, 2087, 2153, 2217, 2274, 2349, 2418, 2488, 2558, 2616, 2686, 2745, 2809, 2869, 2938, 3008, 3071, 3131, 3189, 3258, 3320, 3389, 3446, 3503, 3552, 3613, 3677, 3744, 3788, 3842, 3907, 3966, 4015]}]}
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