Pattern-Selection Based Power Analysis and Discrimination of Low- and High-Grade Myelodysplastic Syndromes Study Using SNP Arrays
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{"title"=>"Pattern-selection based power analysis and discrimination of low- and high-grade myelodysplastic syndromes study using SNP arrays", "type"=>"journal", "authors"=>[{"first_name"=>"Xiaorong", "last_name"=>"Yang", "scopus_author_id"=>"8069891500"}, {"first_name"=>"Xiaobo", "last_name"=>"Zhou", "scopus_author_id"=>"8914487400"}, {"first_name"=>"Wan Ting", "last_name"=>"Huang", "scopus_author_id"=>"8941300300"}, {"first_name"=>"Lingyun", "last_name"=>"Wu", "scopus_author_id"=>"56323329100"}, {"first_name"=>"Federico A.", "last_name"=>"Monzon", "scopus_author_id"=>"55574590000"}, {"first_name"=>"Chung Che", "last_name"=>"Chang", "scopus_author_id"=>"35239708900"}, {"first_name"=>"Stephen T.C.", "last_name"=>"Wong", "scopus_author_id"=>"24726534400"}], "year"=>2009, "source"=>"PLoS ONE", "identifiers"=>{"scopus"=>"2-s2.0-65249129178", "doi"=>"10.1371/journal.pone.0005054", "pui"=>"354493185", "issn"=>"19326203", "pmid"=>"19352488", "sgr"=>"65249129178"}, "id"=>"2e05d79e-5944-3a2f-a2bd-2216e3c01272", "abstract"=>"Copy Number Aberration (CNA) in myelodysplastic syndromes (MDS) study using single nucleotide polymorphism (SNP) arrays have been received increasingly attentions in the recent years. In the current study, a new Constraint Moving Average (CMA) algorithm is adopted to determine the regions of CNA regions first. In addition to large regions of CNA, using the proposed CMA algorithm, small regions of CNA can also be detected. Real-time Polymerase Chain Reaction (qPCR) results prove that the CMA algorithm presents an insightful discovery of both large and subtle regions. Based on the results of CMA, two independent applications are studied. The first one is power analysis for sample estimation. An accurate estimation of sample size needed for the desired purpose of an experiment will be important for effort-efficiency and cost-effectiveness. The power analysis is performed to determine the minimum sample size required for ensuring at least (0<lambda <or=) detected regions statistically different from normal references. As expected, power increase with increasing sample size for a fixed significance level. The second application is the distinguishment of high-grade MDS patients from low-grade ones. We propose to calculate the General Variant Level (GVL) score to integrate the general information of each patient at genotype level, and use it as the unified measurement for the classification. Traditional MDS classifications usually refer to cell morphology and The International Prognostic Scoring System (IPSS), which belongs to the classification at the phenotype level. The proposed GVL score integrates the information of CNA region, the number of abnormal chromosomes and the total number of the altered SNPs at the genotype level. Statistical tests indicate that the high and low grade MDS patients can be well separated by GVL score, which appears to correlate better with clinical outcome than the traditional classification approaches using morphology and IPSS sore at the phenotype level.", "link"=>"http://www.mendeley.com/research/patternselection-based-power-analysis-discrimination-low-highgrade-myelodysplastic-syndromes-study-u", "reader_count"=>7, "reader_count_by_academic_status"=>{"Researcher"=>4, "Student > Postgraduate"=>1, "Professor"=>2}, "reader_count_by_user_role"=>{"Researcher"=>4, "Student > Postgraduate"=>1, "Professor"=>2}, "reader_count_by_subject_area"=>{"Biochemistry, Genetics and Molecular Biology"=>1, "Medicine and Dentistry"=>3, "Agricultural and Biological Sciences"=>3}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>3}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>3}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}}, "group_count"=>0}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/902280"], "description"=>"<p>Power analysis algorithm for the estimation of the minimum sample size.</p>", "links"=>[], "tags"=>["algorithm", "estimation"], "article_id"=>572736, "categories"=>["Genetics"], "users"=>["Xiaorong Yang", "Xiaobo Zhou", "Wan-Ting Huang", "Lingyun Wu", "Federico A. Monzon", "Chung-Che Chang", "Stephen T. C. Wong"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0005054.g003", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Power_analysis_algorithm_for_the_estimation_of_the_minimum_sample_size_/572736", "title"=>"Power analysis algorithm for the estimation of the minimum sample size.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2009-04-08 00:45:36"}
  • {"files"=>["https://ndownloader.figshare.com/files/902675"], "description"=>"<p>(P: Power).</p>", "links"=>[], "tags"=>["estimation", "altered", "regions", "desired"], "article_id"=>573128, "categories"=>["Genetics"], "users"=>["Xiaorong Yang", "Xiaobo Zhou", "Wan-Ting Huang", "Lingyun Wu", "Federico A. Monzon", "Chung-Che Chang", "Stephen T. C. Wong"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0005054.t003", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Sample_size_estimation_to_detect_at_least_0_5_0_6_0_7_and_0_8_truly_altered_regions_for_the_desired_power_up_to_0_8_and_0_9_with_different_significance_level_/573128", "title"=>"Sample size estimation to detect at least , 0.5, 0.6, 0.7 and 0.8 truly altered regions for the desired power up to 0.8 and 0.9, with different significance level.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2009-04-08 00:52:08"}
  • {"files"=>["https://ndownloader.figshare.com/files/902156"], "description"=>"<p>Compared with the references, the regions with circles indicate the CNA regions. For different samples, the CNA regions may occur in the different locations. Some appear repeatedly (the ones with green circles), and some others rarely occur (the ones with red one).</p>", "links"=>[], "tags"=>["regions", "cma"], "article_id"=>572611, "categories"=>["Genetics"], "users"=>["Xiaorong Yang", "Xiaobo Zhou", "Wan-Ting Huang", "Lingyun Wu", "Federico A. Monzon", "Chung-Che Chang", "Stephen T. C. Wong"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0005054.g002", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_CNA_regions_selected_by_CMA_algorithm_/572611", "title"=>"CNA regions selected by CMA algorithm.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2009-04-08 00:43:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/902485"], "description"=>"<p>The cutoff value of copy number one and three in <i>CNAG</i> is −0.35 and 0.35, and the window size of moving average is 5. The <i>t</i>-value is the value of statistics in the <i>t</i> test, and df is the degree of freedom of the test.</p>", "links"=>[], "tags"=>["mds", "variant", "morphology"], "article_id"=>572940, "categories"=>["Genetics"], "users"=>["Xiaorong Yang", "Xiaobo Zhou", "Wan-Ting Huang", "Lingyun Wu", "Federico A. Monzon", "Chung-Che Chang", "Stephen T. C. Wong"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0005054.t005", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Two_group_t_test_results_for_the_discrimination_of_MDS_grade_of_using_General_Variant_Level_score_in_the_sense_of_cell_morphology_and_IPSS_/572940", "title"=>"Two group <i>t</i>-test results for the discrimination of MDS grade of using General Variant Level score in the sense of cell morphology and IPSS.).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2009-04-08 00:49:00"}
  • {"files"=>["https://ndownloader.figshare.com/files/902350"], "description"=>"<p>The significance level is set as 0.05.</p>", "links"=>[], "tags"=>["curves", "estimation", "views"], "article_id"=>572809, "categories"=>["Genetics"], "users"=>["Xiaorong Yang", "Xiaobo Zhou", "Wan-Ting Huang", "Lingyun Wu", "Federico A. Monzon", "Chung-Che Chang", "Stephen T. C. Wong"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0005054.g004", "stats"=>{"downloads"=>1, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Power_curves_and_sample_size_estimation_under_different_views_of_effect_sizes_/572809", "title"=>"Power curves and sample size estimation under different views of effect sizes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2009-04-08 00:46:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/902651"], "description"=>"<p>Three fractions from the same patient are displayed. The Lymphoid is the normal reference. Blast and Erythroid serve as test samples. The log 2 ratio behaviors them are different. As normal one, the log 2 ratio of Lymphoid is closed to 0. There is a significant loss in Erythroid, but for Blast, the log 2 ratio is not low enough. The real time PCR of Lymphoid is normalized as 1. Comparing with the reference, Erythroid is concluded as copy number aberration. However, such abnormality can not be observed in Blast.</p>", "links"=>[], "tags"=>["cma", "algorithm", "located", "chromosome", "7q34", "corresponding", "Real-time", "pcr"], "article_id"=>573095, "categories"=>["Genetics"], "users"=>["Xiaorong Yang", "Xiaobo Zhou", "Wan-Ting Huang", "Lingyun Wu", "Federico A. Monzon", "Chung-Che Chang", "Stephen T. C. Wong"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0005054.t002", "stats"=>{"downloads"=>1, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Output_of_the_CMA_algorithm_results_for_a_region_located_in_chromosome_7q34_and_the_corresponding_real_time_PCR_results_/573095", "title"=>"Output of the CMA algorithm results for a region located in chromosome 7q34 and the corresponding real-time PCR results.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2009-04-08 00:51:35"}
  • {"files"=>["https://ndownloader.figshare.com/files/902456"], "description"=>"<p>A GVL of zero implies that there is no selected abnormal region in the corresponding arrays.</p>", "links"=>[], "tags"=>["gvl", "mds", "patients", "morphology", "ipss"], "article_id"=>572904, "categories"=>["Genetics"], "users"=>["Xiaorong Yang", "Xiaobo Zhou", "Wan-Ting Huang", "Lingyun Wu", "Federico A. Monzon", "Chung-Che Chang", "Stephen T. C. Wong"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0005054.t004", "stats"=>{"downloads"=>1, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_average_GVL_of_MDS_patients_and_the_discrimination_between_the_high_grade_MDS_and_the_low_grade_MDS_by_both_cell_morphology_and_IPSS_score_/572904", "title"=>"The average GVL of MDS patients and the discrimination between the high grade MDS and the low grade MDS by both cell morphology and IPSS score.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2009-04-08 00:48:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/902076"], "description"=>"<p>MDS-2 Lymphoid is the reference, and MDS-2 Erythroid is the test sample. In the test sample, the average log-2 intensities of every five consecutive SNPs in the circled region are higher than 0.35, with the small SDs (< = 0.15). Selected overlapping regions are merged into a large region.</p>", "links"=>[], "tags"=>["cma"], "article_id"=>572533, "categories"=>["Genetics"], "users"=>["Xiaorong Yang", "Xiaobo Zhou", "Wan-Ting Huang", "Lingyun Wu", "Federico A. Monzon", "Chung-Che Chang", "Stephen T. C. Wong"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0005054.g001", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Illustration_of_the_CMA_algorithm_/572533", "title"=>"Illustration of the CMA algorithm.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2009-04-08 00:42:13"}
  • {"files"=>["https://ndownloader.figshare.com/files/902571"], "description"=>"<p>Two-group <i>t</i>-test are performed under the null hypothesis, that mean of two groups are no significant different.</p>", "links"=>[], "tags"=>["aberrations", "cma", "algorithm"], "article_id"=>573027, "categories"=>["Genetics"], "users"=>["Xiaorong Yang", "Xiaobo Zhou", "Wan-Ting Huang", "Lingyun Wu", "Federico A. Monzon", "Chung-Che Chang", "Stephen T. C. Wong"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0005054.t007", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Copy_number_aberrations_comparison_of_CMA_algorithm_and_CNAG_MDS_7_is_excluded_/573027", "title"=>"Copy number aberrations comparison of CMA algorithm and <i>CNAG</i> (MDS-7 is excluded).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2009-04-08 00:50:27"}
  • {"files"=>["https://ndownloader.figshare.com/files/902600"], "description"=>"<p>E.g. there are 3770 genotyping conflicting SNPs, each of which appears in 5 arrays, and if such conflicts are just due to random error (i.e. can not be regarded as wrong genotyping calls), the probability is 0.000977.</p>", "links"=>[], "tags"=>["genotype", "conflicting", "35"], "article_id"=>573058, "categories"=>["Genetics"], "users"=>["Xiaorong Yang", "Xiaobo Zhou", "Wan-Ting Huang", "Lingyun Wu", "Federico A. Monzon", "Chung-Che Chang", "Stephen T. C. Wong"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0005054.t001", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Results_for_genotype_conflicting_analysis_for_35_arrays_/573058", "title"=>"Results for genotype conflicting analysis for 35 arrays.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2009-04-08 00:50:58"}
  • {"files"=>["https://ndownloader.figshare.com/files/902535"], "description"=>"<p>B: Blast; E: Erythroid.</p>", "links"=>[], "tags"=>["abnormal", "regions", "chromosome", "cma", "denote"], "article_id"=>572989, "categories"=>["Genetics"], "users"=>["Xiaorong Yang", "Xiaobo Zhou", "Wan-Ting Huang", "Lingyun Wu", "Federico A. Monzon", "Chung-Che Chang", "Stephen T. C. Wong"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0005054.t006", "stats"=>{"downloads"=>2, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_of_selected_abnormal_regions_in_chromosome_7_by_CMA_algorithm_CNAG_and_CBS_Y_and_N_denote_if_the_region_is_selected_or_not_respectively_/572989", "title"=>"Comparison of selected abnormal regions in chromosome 7 by CMA algorithm, <i>CNAG</i> and CBS. Y and N denote if the region is selected or not, respectively.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2009-04-08 00:49:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/446250", "https://ndownloader.figshare.com/files/446285", "https://ndownloader.figshare.com/files/446320", "https://ndownloader.figshare.com/files/446365"], "description"=>"<div><p>Copy Number Aberration (CNA) in myelodysplastic syndromes (MDS) study using single nucleotide polymorphism (SNP) arrays have been received increasingly attentions in the recent years. In the current study, a new Constraint Moving Average (CMA) algorithm is adopted to determine the regions of CNA regions first. In addition to large regions of CNA, using the proposed CMA algorithm, small regions of CNA can also be detected. Real-time Polymerase Chain Reaction (qPCR) results prove that the CMA algorithm presents an insightful discovery of both large and subtle regions. Based on the results of CMA, two independent applications are studied. The first one is power analysis for sample estimation. An accurate estimation of sample size needed for the desired purpose of an experiment will be important for effort-efficiency and cost-effectiveness. The power analysis is performed to determine the minimum sample size required for ensuring at least () detected regions statistically different from normal references. As expected, power increase with increasing sample size for a fixed significance level. The second application is the distinguishment of high-grade MDS patients from low-grade ones. We propose to calculate the General Variant Level (GVL) score to integrate the general information of each patient at genotype level, and use it as the unified measurement for the classification. Traditional MDS classifications usually refer to cell morphology and The International Prognostic Scoring System (IPSS), which belongs to the classification at the phenotype level. The proposed GVL score integrates the information of CNA region, the number of abnormal chromosomes and the total number of the altered SNPs at the genotype level. Statistical tests indicate that the high and low grade MDS patients can be well separated by GVL score, which appears to correlate better with clinical outcome than the traditional classification approaches using morphology and IPSS sore at the phenotype level.</p></div>", "links"=>[], "tags"=>["pattern-selection", "based", "low-", "high-grade", "myelodysplastic", "syndromes", "snp", "arrays"], "article_id"=>147950, "categories"=>["Genetics"], "users"=>["Xiaorong Yang", "Xiaobo Zhou", "Wan-Ting Huang", "Lingyun Wu", "Federico A. Monzon", "Chung-Che Chang", "Stephen T. C. Wong"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0005054.s001", "https://dx.doi.org/10.1371/journal.pone.0005054.s002", "https://dx.doi.org/10.1371/journal.pone.0005054.s003", "https://dx.doi.org/10.1371/journal.pone.0005054.s004"], "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Pattern_Selection_Based_Power_Analysis_and_Discrimination_of_Low_and_High_Grade_Myelodysplastic_Syndromes_Study_Using_SNP_Arrays/147950", "title"=>"Pattern-Selection Based Power Analysis and Discrimination of Low- and High-Grade Myelodysplastic Syndromes Study Using SNP Arrays", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2009-04-08 02:12:30"}

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  • {"unique-ip"=>"3", "full-text"=>"5", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2013", "month"=>"12"}
  • {"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"=>"2014", "month"=>"1"}
  • {"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"=>"2014", "month"=>"2"}
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  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"6"}
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  • {"unique-ip"=>"1", "full-text"=>"0", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"8"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"9"}
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  • {"unique-ip"=>"3", "full-text"=>"2", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"7"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"8"}
  • {"unique-ip"=>"4", "full-text"=>"3", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"9"}
  • {"unique-ip"=>"21", "full-text"=>"11", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"4", "supp-data"=>"12", "cited-by"=>"0", "year"=>"2014", "month"=>"10"}
  • {"unique-ip"=>"1", "full-text"=>"0", "pdf"=>"1", "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"=>"5", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"11"}
  • {"unique-ip"=>"6", "full-text"=>"5", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"12"}
  • {"unique-ip"=>"6", "full-text"=>"6", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"1"}
  • {"unique-ip"=>"4", "full-text"=>"2", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2015", "month"=>"11"}
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  • {"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"=>"2016", "month"=>"4"}
  • {"unique-ip"=>"3", "full-text"=>"2", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "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"=>"2016", "month"=>"6"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"7"}
  • {"unique-ip"=>"4", "full-text"=>"5", "pdf"=>"0", "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"=>"5", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"9"}
  • {"unique-ip"=>"1", "full-text"=>"0", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"10"}
  • {"unique-ip"=>"2", "full-text"=>"1", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"11"}
  • {"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"=>"2016", "month"=>"12"}
  • {"unique-ip"=>"12", "full-text"=>"4", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2017", "month"=>"1"}
  • {"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"=>"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"=>"4"}
  • {"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"=>"5"}
  • {"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"=>"6"}
  • {"unique-ip"=>"2", "full-text"=>"2", "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"=>"3", "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"=>"2", "full-text"=>"2", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"11"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"12"}
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  • {"unique-ip"=>"13", "full-text"=>"5", "pdf"=>"0", "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"=>"12", "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"=>"4", "full-text"=>"3", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"4"}
  • {"unique-ip"=>"4", "full-text"=>"3", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"6"}
  • {"unique-ip"=>"4", "full-text"=>"2", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"6", "cited-by"=>"0", "year"=>"2018", "month"=>"7"}
  • {"unique-ip"=>"3", "full-text"=>"3", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"8"}
  • {"unique-ip"=>"10", "full-text"=>"8", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"4", "cited-by"=>"0", "year"=>"2018", "month"=>"11"}
  • {"unique-ip"=>"3", "full-text"=>"3", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"9"}
  • {"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"=>"12"}
  • {"unique-ip"=>"5", "full-text"=>"5", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"2"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"4"}
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Relative Metric

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