Sources of Variability in Metabolite Measurements from Urinary Samples
Events
Loading … Spinner

Mendeley | Further Information

{"title"=>"Sources of variability in metabolite measurements from urinary samples", "type"=>"journal", "authors"=>[{"first_name"=>"Qian", "last_name"=>"Xiao", "scopus_author_id"=>"55667639500"}, {"first_name"=>"Steven C.", "last_name"=>"Moore", "scopus_author_id"=>"8867509100"}, {"first_name"=>"Simina M.", "last_name"=>"Boca", "scopus_author_id"=>"21740680900"}, {"first_name"=>"Charles E.", "last_name"=>"Matthews", "scopus_author_id"=>"7201785720"}, {"first_name"=>"Nathaniel", "last_name"=>"Rothman", "scopus_author_id"=>"7005049561"}, {"first_name"=>"Rachael Z.", "last_name"=>"Stolzenberg-Solomon", "scopus_author_id"=>"6701861730"}, {"first_name"=>"Rashmi", "last_name"=>"Sinha", "scopus_author_id"=>"7402857340"}, {"first_name"=>"Amanda J.", "last_name"=>"Cross", "scopus_author_id"=>"7202735866"}, {"first_name"=>"Joshua N.", "last_name"=>"Sampson", "scopus_author_id"=>"9733825800"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"scopus"=>"2-s2.0-84900426981", "doi"=>"10.1371/journal.pone.0095749", "sgr"=>"84900426981", "isbn"=>"1932-6203", "pmid"=>"24788433", "issn"=>"19326203", "pui"=>"373071753"}, "id"=>"55690447-3f7a-3ae0-b598-2aca49fb1097", "abstract"=>"Background: The application of metabolomics in epidemiological studies would potentially allow researchers to identify biomarkers associated with exposures and diseases. However, within-individual variability of metabolite levels caused by temporal variation of metabolites, together with technical variability introduced by laboratory procedures, may reduce the study power to detect such associations. We assessed the sources of variability of metabolites from urine samples and the implications for designing epidemiologic studies. Methods: We measured 539 metabolites in urine samples from the Navy Colon Adenoma Study using liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectroscopy (GC-MS). The study collected 2–3 samples per person from 17 male subjects (age 38–70) over 2–10 days. We estimated between-individual, withinindividual, and technical variability and calculated expected study power with a specific focus on large case-control and nested case-control studies. Results: Overall technical reliability was high (median intraclass correlation = 0.92), and for 72% of the metabolites, the majority of total variance can be attributed to between-individual variability. Age, gender and body mass index explained only a small proportion of the total metabolite variability. For a relative risk (comparing upper and lower quartiles of ‘‘usual’’ levels) of 1.5, we estimated that a study with 500, 1,000, and 5,000 individuals could detect 1.0%, 4.5% and 75% of the metabolite associations. Conclusions: The use of metabolomics in urine samples from epidemiological studies would require large sample sizes to detect associations with moderate effect sizes.", "link"=>"http://www.mendeley.com/research/sources-variability-metabolite-measurements-urinary-samples", "reader_count"=>24, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>4, "Librarian"=>1, "Researcher"=>6, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>5, "Student > Master"=>3, "Other"=>1, "Student > Bachelor"=>1, "Lecturer > Senior Lecturer"=>1}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>4, "Librarian"=>1, "Researcher"=>6, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>5, "Student > Master"=>3, "Other"=>1, "Student > Bachelor"=>1, "Lecturer > Senior Lecturer"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>1, "Environmental Science"=>1, "Biochemistry, Genetics and Molecular Biology"=>4, "Agricultural and Biological Sciences"=>5, "Medicine and Dentistry"=>6, "Veterinary Science and Veterinary Medicine"=>1, "Pharmacology, Toxicology and Pharmaceutical Science"=>1, "Chemistry"=>3, "Social Sciences"=>1, "Computer Science"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>6}, "Chemistry"=>{"Chemistry"=>3}, "Social Sciences"=>{"Social Sciences"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>5}, "Computer Science"=>{"Computer Science"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>4}, "Unspecified"=>{"Unspecified"=>1}, "Environmental Science"=>{"Environmental Science"=>1}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>1}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>1}}, "reader_count_by_country"=>{"Belgium"=>1, "United Kingdom"=>1, "Croatia"=>1}, "group_count"=>1}

Scopus | Further Information

{"@_fa"=>"true", "link"=>[{"@_fa"=>"true", "@ref"=>"self", "@href"=>"https://api.elsevier.com/content/abstract/scopus_id/84900426981"}, {"@_fa"=>"true", "@ref"=>"author-affiliation", "@href"=>"https://api.elsevier.com/content/abstract/scopus_id/84900426981?field=author,affiliation"}, {"@_fa"=>"true", "@ref"=>"scopus", "@href"=>"https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84900426981&origin=inward"}, {"@_fa"=>"true", "@ref"=>"scopus-citedby", "@href"=>"https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=84900426981&origin=inward"}], "prism:url"=>"https://api.elsevier.com/content/abstract/scopus_id/84900426981", "dc:identifier"=>"SCOPUS_ID:84900426981", "eid"=>"2-s2.0-84900426981", "dc:title"=>"Sources of variability in metabolite measurements from urinary samples", "dc:creator"=>"Xiao Q.", "prism:publicationName"=>"PLoS ONE", "prism:eIssn"=>"19326203", "prism:volume"=>"9", "prism:issueIdentifier"=>"5", "prism:pageRange"=>nil, "prism:coverDate"=>"2014-05-01", "prism:coverDisplayDate"=>"1 May 2014", "prism:doi"=>"10.1371/journal.pone.0095749", "citedby-count"=>"13", "affiliation"=>[{"@_fa"=>"true", "affilname"=>"National Cancer Institute", "affiliation-city"=>"Bethesda", "affiliation-country"=>"United States"}], "pubmed-id"=>"24788433", "prism:aggregationType"=>"Journal", "subtype"=>"ar", "subtypeDescription"=>"Article", "article-number"=>"e95749", "source-id"=>"10600153309", "openaccess"=>"1", "openaccessFlag"=>true}

Facebook

  • {"url"=>"http%3A%2F%2Fjournals.plos.org%2Fplosone%2Farticle%3Fid%3D10.1371%252Fjournal.pone.0095749", "share_count"=>0, "like_count"=>0, "comment_count"=>0, "click_count"=>0, "total_count"=>0}

Counter

  • {"month"=>"5", "year"=>"2014", "pdf_views"=>"66", "xml_views"=>"4", "html_views"=>"176"}
  • {"month"=>"6", "year"=>"2014", "pdf_views"=>"15", "xml_views"=>"1", "html_views"=>"58"}
  • {"month"=>"7", "year"=>"2014", "pdf_views"=>"10", "xml_views"=>"0", "html_views"=>"34"}
  • {"month"=>"8", "year"=>"2014", "pdf_views"=>"16", "xml_views"=>"2", "html_views"=>"31"}
  • {"month"=>"9", "year"=>"2014", "pdf_views"=>"15", "xml_views"=>"1", "html_views"=>"39"}
  • {"month"=>"10", "year"=>"2014", "pdf_views"=>"11", "xml_views"=>"1", "html_views"=>"33"}
  • {"month"=>"11", "year"=>"2014", "pdf_views"=>"10", "xml_views"=>"1", "html_views"=>"28"}
  • {"month"=>"12", "year"=>"2014", "pdf_views"=>"11", "xml_views"=>"3", "html_views"=>"33"}
  • {"month"=>"1", "year"=>"2015", "pdf_views"=>"16", "xml_views"=>"0", "html_views"=>"22"}
  • {"month"=>"2", "year"=>"2015", "pdf_views"=>"5", "xml_views"=>"0", "html_views"=>"25"}
  • {"month"=>"3", "year"=>"2015", "pdf_views"=>"9", "xml_views"=>"0", "html_views"=>"24"}
  • {"month"=>"4", "year"=>"2015", "pdf_views"=>"6", "xml_views"=>"1", "html_views"=>"25"}
  • {"month"=>"5", "year"=>"2015", "pdf_views"=>"5", "xml_views"=>"0", "html_views"=>"12"}
  • {"month"=>"6", "year"=>"2015", "pdf_views"=>"4", "xml_views"=>"0", "html_views"=>"21"}
  • {"month"=>"7", "year"=>"2015", "pdf_views"=>"7", "xml_views"=>"0", "html_views"=>"20"}
  • {"month"=>"8", "year"=>"2015", "pdf_views"=>"2", "xml_views"=>"0", "html_views"=>"22"}
  • {"month"=>"9", "year"=>"2015", "pdf_views"=>"5", "xml_views"=>"1", "html_views"=>"21"}
  • {"month"=>"10", "year"=>"2015", "pdf_views"=>"11", "xml_views"=>"0", "html_views"=>"38"}
  • {"month"=>"11", "year"=>"2015", "pdf_views"=>"8", "xml_views"=>"0", "html_views"=>"21"}
  • {"month"=>"12", "year"=>"2015", "pdf_views"=>"6", "xml_views"=>"0", "html_views"=>"18"}
  • {"month"=>"1", "year"=>"2016", "pdf_views"=>"6", "xml_views"=>"0", "html_views"=>"17"}
  • {"month"=>"2", "year"=>"2016", "pdf_views"=>"2", "xml_views"=>"0", "html_views"=>"9"}
  • {"month"=>"3", "year"=>"2016", "pdf_views"=>"6", "xml_views"=>"0", "html_views"=>"25"}
  • {"month"=>"4", "year"=>"2016", "pdf_views"=>"4", "xml_views"=>"0", "html_views"=>"21"}
  • {"month"=>"5", "year"=>"2016", "pdf_views"=>"4", "xml_views"=>"0", "html_views"=>"13"}
  • {"month"=>"6", "year"=>"2016", "pdf_views"=>"7", "xml_views"=>"0", "html_views"=>"20"}
  • {"month"=>"7", "year"=>"2016", "pdf_views"=>"12", "xml_views"=>"0", "html_views"=>"18"}
  • {"month"=>"8", "year"=>"2016", "pdf_views"=>"4", "xml_views"=>"0", "html_views"=>"15"}
  • {"month"=>"9", "year"=>"2016", "pdf_views"=>"13", "xml_views"=>"0", "html_views"=>"33"}
  • {"month"=>"10", "year"=>"2016", "pdf_views"=>"8", "xml_views"=>"0", "html_views"=>"29"}
  • {"month"=>"11", "year"=>"2016", "pdf_views"=>"2", "xml_views"=>"0", "html_views"=>"23"}
  • {"month"=>"12", "year"=>"2016", "pdf_views"=>"9", "xml_views"=>"0", "html_views"=>"23"}
  • {"month"=>"1", "year"=>"2017", "pdf_views"=>"1", "xml_views"=>"0", "html_views"=>"17"}
  • {"month"=>"2", "year"=>"2017", "pdf_views"=>"4", "xml_views"=>"0", "html_views"=>"29"}
  • {"month"=>"3", "year"=>"2017", "pdf_views"=>"2", "xml_views"=>"0", "html_views"=>"21"}
  • {"month"=>"4", "year"=>"2017", "pdf_views"=>"4", "xml_views"=>"0", "html_views"=>"26"}
  • {"month"=>"5", "year"=>"2017", "pdf_views"=>"3", "xml_views"=>"0", "html_views"=>"33"}
  • {"month"=>"6", "year"=>"2017", "pdf_views"=>"10", "xml_views"=>"0", "html_views"=>"31"}
  • {"month"=>"7", "year"=>"2017", "pdf_views"=>"7", "xml_views"=>"3", "html_views"=>"26"}
  • {"month"=>"8", "year"=>"2017", "pdf_views"=>"6", "xml_views"=>"2", "html_views"=>"27"}
  • {"month"=>"9", "year"=>"2017", "pdf_views"=>"24", "xml_views"=>"1", "html_views"=>"29"}
  • {"month"=>"10", "year"=>"2017", "pdf_views"=>"3", "xml_views"=>"1", "html_views"=>"30"}
  • {"month"=>"11", "year"=>"2017", "pdf_views"=>"2", "xml_views"=>"0", "html_views"=>"63"}
  • {"month"=>"12", "year"=>"2017", "pdf_views"=>"3", "xml_views"=>"2", "html_views"=>"30"}
  • {"month"=>"1", "year"=>"2018", "pdf_views"=>"3", "xml_views"=>"1", "html_views"=>"22"}
  • {"month"=>"2", "year"=>"2018", "pdf_views"=>"6", "xml_views"=>"0", "html_views"=>"14"}
  • {"month"=>"3", "year"=>"2018", "pdf_views"=>"1", "xml_views"=>"1", "html_views"=>"8"}
  • {"month"=>"4", "year"=>"2018", "pdf_views"=>"7", "xml_views"=>"0", "html_views"=>"15"}
  • {"month"=>"5", "year"=>"2018", "pdf_views"=>"0", "xml_views"=>"1", "html_views"=>"14"}
  • {"month"=>"6", "year"=>"2018", "pdf_views"=>"13", "xml_views"=>"0", "html_views"=>"14"}
  • {"month"=>"7", "year"=>"2018", "pdf_views"=>"3", "xml_views"=>"3", "html_views"=>"10"}
  • {"month"=>"8", "year"=>"2018", "pdf_views"=>"6", "xml_views"=>"1", "html_views"=>"13"}
  • {"month"=>"9", "year"=>"2018", "pdf_views"=>"8", "xml_views"=>"0", "html_views"=>"11"}
  • {"month"=>"10", "year"=>"2018", "pdf_views"=>"3", "xml_views"=>"1", "html_views"=>"18"}
  • {"month"=>"11", "year"=>"2018", "pdf_views"=>"2", "xml_views"=>"0", "html_views"=>"13"}
  • {"month"=>"12", "year"=>"2018", "pdf_views"=>"1", "xml_views"=>"0", "html_views"=>"8"}
  • {"month"=>"1", "year"=>"2019", "pdf_views"=>"1", "xml_views"=>"0", "html_views"=>"17"}
  • {"month"=>"2", "year"=>"2019", "pdf_views"=>"3", "xml_views"=>"0", "html_views"=>"20"}
  • {"month"=>"3", "year"=>"2019", "pdf_views"=>"3", "xml_views"=>"0", "html_views"=>"16"}
  • {"month"=>"4", "year"=>"2019", "pdf_views"=>"5", "xml_views"=>"0", "html_views"=>"12"}
  • {"month"=>"5", "year"=>"2019", "pdf_views"=>"7", "xml_views"=>"0", "html_views"=>"14"}

Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1481954"], "description"=>"<p>The ICC is a measure of laboratory variability. The is a measure of between-individual variance. The curves illustrate the ICC and for the specified metabolite quantile ranking. Median ICC: 0.92. Median : 0.62.</p>", "links"=>[], "tags"=>["epidemiology", "Biomarker epidemiology", "Epidemiological methods and statistics", "iccs", "urinary", "samples", "navy", "colon", "adenoma"], "article_id"=>1013790, "categories"=>["Biological Sciences"], "users"=>["Qian Xiao", "Steven C. Moore", "Simina M. Boca", "Charles E. Matthews", "Nathaniel Rothman", "Rachael Z. Stolzenberg-Solomon", "Rashmi Sinha", "Amanda J. Cross", "Joshua N. Sampson"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0095749.g001", "stats"=>{"downloads"=>1, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_plots_illustrate_the_distribution_of_technical_ICCs_A_and_B_of_overnight_urinary_samples_in_the_Navy_Colon_Adenoma_Study_/1013790", "title"=>"The plots illustrate the distribution of technical ICCs (A) and (B) of overnight urinary samples in the Navy Colon Adenoma Study.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-05-01 03:56:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/1481965"], "description"=>"a<p>The naïve estimates of true relative risks of 1.5, 3.0 and 5.0 would be 1.4, 2.3 and 3.4, respectively.</p>", "links"=>[], "tags"=>["epidemiology", "Biomarker epidemiology", "Epidemiological methods and statistics", "associations", "metabolites", "case-control", "risks"], "article_id"=>1013801, "categories"=>["Biological Sciences"], "users"=>["Qian Xiao", "Steven C. Moore", "Simina M. Boca", "Charles E. Matthews", "Nathaniel Rothman", "Rachael Z. Stolzenberg-Solomon", "Rashmi Sinha", "Amanda J. Cross", "Joshua N. Sampson"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0095749.t003", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Average_study_power_to_detect_associations_between_metabolites_and_disease_in_a_case_control_study_according_to_different_relative_risks_and_sample_sizes_/1013801", "title"=>"Average study power to detect associations between metabolites and disease in a case-control study according to different relative risks and sample sizes.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-05-01 03:56:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/1481963"], "description"=>"a<p>adjusted for age (quartiles), gender (male, female) and BMI (<25, 25–<30 and 30+kg/m<sup>2</sup>).</p>", "links"=>[], "tags"=>["epidemiology", "Biomarker epidemiology", "Epidemiological methods and statistics", "metabolites", "highest", "lowest", "within-subject", "navy", "colon", "adenoma"], "article_id"=>1013799, "categories"=>["Biological Sciences"], "users"=>["Qian Xiao", "Steven C. Moore", "Simina M. Boca", "Charles E. Matthews", "Nathaniel Rothman", "Rachael Z. Stolzenberg-Solomon", "Rashmi Sinha", "Amanda J. Cross", "Joshua N. Sampson"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0095749.t002", "stats"=>{"downloads"=>1, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_A_list_of_identified_metabolites_with_the_highest_values_of_between_subject_variability_e_g_the_lowest_within_subject_variability_among_all_metabolites_in_the_Navy_Colon_Adenoma_Study_/1013799", "title"=>"A list of identified metabolites with the highest values of between subject variability, (e.g., the lowest within-subject variability), among all metabolites in the Navy Colon Adenoma Study.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-05-01 03:56:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/1481962"], "description"=>"a<p>Each row list the percentage of metabolites with an estimated parameter (ICC, and ) exceeding the threshold of 0.2, 0.5 and 0.8.</p>b<p>ICC represents the proportion of total variation attributable to biological variance.</p>c<p> represents the proportion of biological variability attributable to between-individual variance.</p>d<p> represents the proportion of total variation attributable to between-individual variance.</p>", "links"=>[], "tags"=>["epidemiology", "Biomarker epidemiology", "Epidemiological methods and statistics", "metabolites", "exceeding", "parameter", "navy", "colon", "adenoma"], "article_id"=>1013798, "categories"=>["Biological Sciences"], "users"=>["Qian Xiao", "Steven C. Moore", "Simina M. Boca", "Charles E. Matthews", "Nathaniel Rothman", "Rachael Z. Stolzenberg-Solomon", "Rashmi Sinha", "Amanda J. Cross", "Joshua N. Sampson"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0095749.t001", "stats"=>{"downloads"=>4, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Percentage_of_metabolites_exceeding_parameter_thresholds_a_in_the_Navy_Colon_Adenoma_Study_/1013798", "title"=>"Percentage of metabolites exceeding parameter thresholds<sup>a</sup> in the Navy Colon Adenoma Study.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-05-01 03:56:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/1481966"], "description"=>"<div><p>Background</p><p>The application of metabolomics in epidemiological studies would potentially allow researchers to identify biomarkers associated with exposures and diseases. However, within-individual variability of metabolite levels caused by temporal variation of metabolites, together with technical variability introduced by laboratory procedures, may reduce the study power to detect such associations. We assessed the sources of variability of metabolites from urine samples and the implications for designing epidemiologic studies.</p><p>Methods</p><p>We measured 539 metabolites in urine samples from the Navy Colon Adenoma Study using liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectroscopy (GC-MS). The study collected 2–3 samples per person from 17 male subjects (age 38–70) over 2–10 days. We estimated between-individual, within-individual, and technical variability and calculated expected study power with a specific focus on large case-control and nested case-control studies.</p><p>Results</p><p>Overall technical reliability was high (median intraclass correlation = 0.92), and for 72% of the metabolites, the majority of total variance can be attributed to between-individual variability. Age, gender and body mass index explained only a small proportion of the total metabolite variability. For a relative risk (comparing upper and lower quartiles of “usual” levels) of 1.5, we estimated that a study with 500, 1,000, and 5,000 individuals could detect 1.0%, 4.5% and 75% of the metabolite associations.</p><p>Conclusions</p><p>The use of metabolomics in urine samples from epidemiological studies would require large sample sizes to detect associations with moderate effect sizes.</p></div>", "links"=>[], "tags"=>["epidemiology", "Biomarker epidemiology", "Epidemiological methods and statistics", "variability", "metabolite", "urinary"], "article_id"=>1013802, "categories"=>["Biological Sciences"], "users"=>["Qian Xiao", "Steven C. Moore", "Simina M. Boca", "Charles E. Matthews", "Nathaniel Rothman", "Rachael Z. Stolzenberg-Solomon", "Rashmi Sinha", "Amanda J. Cross", "Joshua N. Sampson"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0095749", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Sources_of_Variability_in_Metabolite_Measurements_from_Urinary_Samples_/1013802", "title"=>"Sources of Variability in Metabolite Measurements from Urinary Samples", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-05-01 03:56:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/1481961"], "description"=>"<p>Effect size is defined by the relative risk (RR, on the x-axis) of disease comparing individuals in the top and bottom quartiles of the “usual” metabolite level. The top axis shows the naïve relative risk that would be observed in the study without adjusting for measurement error. Each figure varies one parameter: sample size, α-level, or the number of samples/individual. (A) presents power curves according to different sample size (n of 500, 1,000 and 5,000) under a Bonferroni-adjusted α-levels (0.05/539); (B) presents power curves with different α-levels in a case-control study of 1,000 individuals; (C) presents power curves in a case-control study of 1,000 individuals, with different number of distinct urinary samples (1, 3, and 10, α-level = 0.05/539).</p>", "links"=>[], "tags"=>["epidemiology", "Biomarker epidemiology", "Epidemiological methods and statistics", "curves", "metabolites"], "article_id"=>1013797, "categories"=>["Biological Sciences"], "users"=>["Qian Xiao", "Steven C. Moore", "Simina M. Boca", "Charles E. Matthews", "Nathaniel Rothman", "Rachael Z. Stolzenberg-Solomon", "Rashmi Sinha", "Amanda J. Cross", "Joshua N. Sampson"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0095749.g004", "stats"=>{"downloads"=>1, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_curves_show_the_proportion_of_metabolites_expected_to_be_detected_in_a_case_control_study_as_a_function_of_effect_size_/1013797", "title"=>"The curves show the proportion of metabolites expected to be detected in a case control study as a function of effect size.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-05-01 03:56:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/1481957"], "description"=>"<p>The x-axis represents the metabolite quantile ranking, and the y-axis represents . The black areas under the curve illustrate the for the specified metabolite quantile ranking, which shows the variance explained by these three covariates.</p>", "links"=>[], "tags"=>["epidemiology", "Biomarker epidemiology", "Epidemiological methods and statistics"], "article_id"=>1013793, "categories"=>["Biological Sciences"], "users"=>["Qian Xiao", "Steven C. Moore", "Simina M. Boca", "Charles E. Matthews", "Nathaniel Rothman", "Rachael Z. Stolzenberg-Solomon", "Rashmi Sinha", "Amanda J. Cross", "Joshua N. Sampson"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0095749.g003", "stats"=>{"downloads"=>2, "page_views"=>36, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_distribution_of_A_B_and_C_/1013793", "title"=>"The distribution of (A), (B), and (C).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-05-01 03:56:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/1481955"], "description"=>"<p>The curve illustrates that the majority of ρ are likely above 0 and that measurements collected on consecutive days are likely more similar than those collected one week apart. The x-axis indicates the quantile ranking and y-axis indicates for a metabolite at that ranking. For example, the median level, that of the metabolite ranked 284, is 0.49.</p>", "links"=>[], "tags"=>["epidemiology", "Biomarker epidemiology", "Epidemiological methods and statistics", "illustrates", "autocorrelation"], "article_id"=>1013791, "categories"=>["Biological Sciences"], "users"=>["Qian Xiao", "Steven C. Moore", "Simina M. Boca", "Charles E. Matthews", "Nathaniel Rothman", "Rachael Z. Stolzenberg-Solomon", "Rashmi Sinha", "Amanda J. Cross", "Joshua N. Sampson"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0095749.g002", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_plot_illustrates_the_distribution_of_an_estimate_of_a_measure_of_autocorrelation_over_time_for_all_metabolites_/1013791", "title"=>"The plot illustrates the distribution of , an estimate of a measure of autocorrelation over time, for all metabolites.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-05-01 03:56:49"}

PMC Usage Stats | Further Information

  • {"unique-ip"=>"21", "full-text"=>"17", "pdf"=>"12", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"5"}
  • {"unique-ip"=>"27", "full-text"=>"28", "pdf"=>"15", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"6"}
  • {"unique-ip"=>"14", "full-text"=>"16", "pdf"=>"8", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"4"}
  • {"unique-ip"=>"11", "full-text"=>"19", "pdf"=>"7", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"5"}
  • {"unique-ip"=>"6", "full-text"=>"6", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"8", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2015", "month"=>"6"}
  • {"unique-ip"=>"8", "full-text"=>"8", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"7"}
  • {"unique-ip"=>"12", "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"=>"3"}
  • {"unique-ip"=>"11", "full-text"=>"8", "pdf"=>"8", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"2"}
  • {"unique-ip"=>"6", "full-text"=>"4", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2015", "month"=>"8"}
  • {"unique-ip"=>"8", "full-text"=>"8", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2015", "month"=>"9"}
  • {"unique-ip"=>"9", "full-text"=>"9", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2015", "month"=>"10"}
  • {"unique-ip"=>"12", "full-text"=>"11", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"7"}
  • {"unique-ip"=>"10", "full-text"=>"8", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"8"}
  • {"unique-ip"=>"18", "full-text"=>"12", "pdf"=>"11", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"9"}
  • {"unique-ip"=>"9", "full-text"=>"8", "pdf"=>"10", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"10"}
  • {"unique-ip"=>"6", "full-text"=>"7", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"2"}
  • {"unique-ip"=>"8", "full-text"=>"7", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"11"}
  • {"unique-ip"=>"6", "full-text"=>"4", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"12"}
  • {"unique-ip"=>"5", "full-text"=>"5", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"1"}
  • {"unique-ip"=>"18", "full-text"=>"17", "pdf"=>"12", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"4", "year"=>"2015", "month"=>"11"}
  • {"unique-ip"=>"14", "full-text"=>"9", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"8", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"12"}
  • {"unique-ip"=>"4", "full-text"=>"7", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2016", "month"=>"1"}
  • {"unique-ip"=>"9", "full-text"=>"10", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"3"}
  • {"unique-ip"=>"21", "full-text"=>"14", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"4", "supp-data"=>"1", "cited-by"=>"1", "year"=>"2016", "month"=>"4"}
  • {"unique-ip"=>"7", "full-text"=>"7", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"5"}
  • {"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"=>"2016", "month"=>"6"}
  • {"unique-ip"=>"5", "full-text"=>"5", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"7"}
  • {"unique-ip"=>"3", "full-text"=>"3", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"8"}
  • {"unique-ip"=>"6", "full-text"=>"6", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"9"}
  • {"unique-ip"=>"10", "full-text"=>"10", "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"=>"3", "full-text"=>"3", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"11"}
  • {"unique-ip"=>"11", "full-text"=>"9", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"12"}
  • {"unique-ip"=>"3", "full-text"=>"3", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"1"}
  • {"unique-ip"=>"4", "full-text"=>"5", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"2"}
  • {"unique-ip"=>"3", "full-text"=>"3", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"3"}
  • {"unique-ip"=>"7", "full-text"=>"9", "pdf"=>"10", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"4"}
  • {"unique-ip"=>"7", "full-text"=>"5", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"5"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"6"}
  • {"unique-ip"=>"3", "full-text"=>"3", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"7"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"8"}
  • {"unique-ip"=>"6", "full-text"=>"5", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2017", "month"=>"9"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"10"}
  • {"unique-ip"=>"4", "full-text"=>"4", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"5", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"11"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"12"}
  • {"unique-ip"=>"4", "full-text"=>"6", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"1"}
  • {"unique-ip"=>"5", "full-text"=>"6", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"3"}
  • {"unique-ip"=>"14", "full-text"=>"14", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2019", "month"=>"1"}
  • {"unique-ip"=>"7", "full-text"=>"6", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"11"}
  • {"unique-ip"=>"7", "full-text"=>"8", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"9"}
  • {"unique-ip"=>"10", "full-text"=>"11", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"4"}
  • {"unique-ip"=>"9", "full-text"=>"12", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"5"}
  • {"unique-ip"=>"5", "full-text"=>"5", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"6"}
  • {"unique-ip"=>"9", "full-text"=>"11", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2018", "month"=>"7"}
  • {"unique-ip"=>"4", "full-text"=>"4", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"8"}
  • {"unique-ip"=>"5", "full-text"=>"5", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"10"}
  • {"unique-ip"=>"19", "full-text"=>"11", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"4", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"12"}
  • {"unique-ip"=>"10", "full-text"=>"13", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"2"}
  • {"unique-ip"=>"11", "full-text"=>"8", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"3"}
  • {"unique-ip"=>"4", "full-text"=>"3", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"4"}

Relative Metric

{"start_date"=>"2014-01-01T00:00:00Z", "end_date"=>"2014-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences/Anatomy", "average_usage"=>[267]}, {"subject_area"=>"/Biology and life sciences/Physiology", "average_usage"=>[280]}, {"subject_area"=>"/Medicine and health sciences/Pharmacology", "average_usage"=>[286]}, {"subject_area"=>"/Medicine and health sciences/Physiology", "average_usage"=>[278]}]}
Loading … Spinner
There are currently no alerts