The Evolutionary Analysis of Emerging Low Frequency HIV-1 CXCR4 Using Variants through Time—An Ultra-Deep Approach
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{"title"=>"The evolutionary analysis of emerging low frequency HIV-1 CXCR4 using variants through time-an ultra-deep approach", "type"=>"journal", "authors"=>[{"first_name"=>"John", "last_name"=>"Archer", "scopus_author_id"=>"35892365000"}, {"first_name"=>"Andrew", "last_name"=>"Rambaut", "scopus_author_id"=>"7004230842"}, {"first_name"=>"Bruce E.", "last_name"=>"Taillon", "scopus_author_id"=>"6602430885"}, {"first_name"=>"P.", "last_name"=>"Richard Harrigan", "scopus_author_id"=>"7004857656"}, {"first_name"=>"Marilyn", "last_name"=>"Lewis", "scopus_author_id"=>"36055590300"}, {"first_name"=>"David L.", "last_name"=>"Robertson", "scopus_author_id"=>"7402818741"}], "year"=>2010, "source"=>"PLoS Computational Biology", "identifiers"=>{"scopus"=>"2-s2.0-78651228163", "pmid"=>"21187908", "sgr"=>"78651228163", "doi"=>"10.1371/journal.pcbi.1001022", "isbn"=>"1553-7358 (Electronic)\\r1553-734X (Linking)", "issn"=>"1553734X", "pui"=>"361077251"}, "id"=>"ccddc6d6-ab9f-3a3f-8f6a-2d13a78b6db3", "abstract"=>"Large-scale parallel pyrosequencing produces unprecedented quantities of sequence data. However, when generated from viral populations current mapping software is inadequate for dealing with the high levels of variation present, resulting in the potential for biased data loss. In order to apply the 454 Life Sciences' pyrosequencing system to the study of viral populations, we have developed software for the processing of highly variable sequence data. Here we demonstrate our software by analyzing two temporally sampled HIV-1 intra-patient datasets from a clinical study of maraviroc. This drug binds the CCR5 coreceptor, thus preventing HIV-1 infection of the cell. The objective is to determine viral tropism (CCR5 versus CXCR4 usage) and track the evolution of minority CXCR4-using variants that may limit the response to a maraviroc-containing treatment regimen. Five time points (two prior to treatment) were available from each patient. We first quantify the effects of divergence on initial read k-mer mapping and demonstrate the importance of utilizing population-specific template sequences in relation to the analysis of next-generation sequence data. Then, in conjunction with coreceptor prediction algorithms that infer HIV tropism, our software was used to quantify the viral population structure pre- and post-treatment. In both cases, low frequency CXCR4-using variants (2.5-15%) were detected prior to treatment. Following phylogenetic inference, these variants were observed to exist as distinct lineages that were maintained through time. Our analysis, thus confirms the role of pre-existing CXCR4-using virus in the emergence of maraviroc-insensitive HIV. The software will have utility for the study of intra-host viral diversity and evolution of other fast evolving viruses, and is available from http://www.bioinf.manchester.ac.uk/segminator/.", "link"=>"http://www.mendeley.com/research/evolutionary-analysis-emerging-low-frequency-hiv1-cxcr4-using-variants-through-timean-ultradeep-appr", "reader_count"=>94, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>9, "Librarian"=>1, "Researcher"=>31, "Student > Doctoral Student"=>3, "Student > Ph. D. Student"=>21, "Student > Postgraduate"=>2, "Other"=>6, "Student > Master"=>6, "Student > Bachelor"=>5, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>1, "Professor"=>6, "Unspecified"=>1}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>9, "Librarian"=>1, "Researcher"=>31, "Student > Doctoral Student"=>3, "Student > Ph. D. Student"=>21, "Student > Postgraduate"=>2, "Other"=>6, "Student > Master"=>6, "Student > Bachelor"=>5, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>1, "Professor"=>6, "Unspecified"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>4, "Engineering"=>1, "Biochemistry, Genetics and Molecular Biology"=>7, "Mathematics"=>1, "Agricultural and Biological Sciences"=>56, "Medicine and Dentistry"=>14, "Veterinary Science and Veterinary Medicine"=>1, "Physics and Astronomy"=>2, "Computer Science"=>6, "Immunology and Microbiology"=>2}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>14}, "Physics and Astronomy"=>{"Physics and Astronomy"=>2}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>2}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>56}, "Computer Science"=>{"Computer Science"=>6}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>7}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>4}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>1}}, "reader_count_by_country"=>{"Canada"=>1, "Sweden"=>2, "Netherlands"=>1, "Belgium"=>1, "United States"=>3, "Brazil"=>1, "United Kingdom"=>2, "France"=>1, "Switzerland"=>1, "Germany"=>1, "Spain"=>1}, "group_count"=>4}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/811295"], "description"=>"<p>As divergence from the consensus template increases the number of reads successfully mapped decreases. Each box and whisker (1.5 times the inter-quartile range) represents 50 repetitions of the mapping process at the level of divergence indicated on the x-axis. The bottom circle, on the y-axis, indicates the percentage of reads mapped to HXB2 in relation to the total number mapped to the consensus template (top circle). The dataset used for this comparison was patient D at screening.</p>", "links"=>[], "tags"=>["k-mer"], "article_id"=>481664, "categories"=>["Medicine", "Evolutionary Biology", "Cancer", "Plant Biology"], "users"=>["John Archer", "Andrew Rambaut", "Bruce E. Taillon", "P. Richard Harrigan", "Marilyn Lewis", "David L. Robertson"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1001022.g002", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Relationship_between_k_mer_mapping_and_diversity_/481664", "title"=>"Relationship between k-mer mapping and diversity.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-12-16 00:27:44"}
  • {"files"=>["https://ndownloader.figshare.com/files/811235"], "description"=>"<p>On the left hand side the preprocessing of the template sequence prior to read mapping is illustrated. The fragments titled “k-mers” are all the unique words (length = 5) within the template sequence. These are stored along with their corresponding locations. On the opposite side all k-mers of equal length, extracted from the read, are shown. The plot indicates the frequency of k-mer matches across the template sequence for a single read. Grey boxes indicate processing events that take place within the framework. The yellow circles indicate optimization steps: (i) only exact k-mer matches used (ii) a heuristic alignment not constructed from the k-mer matching (just the k-mer match frequencies are plotted) and (iii) only the appropriate region of the template is pairwise aligned to the read.</p>", "links"=>[], "tags"=>["computational biology/comparative sequence analysis", "computer science/applications", "evolutionary biology/bioinformatics", "infectious diseases/hiv infection and aids", "virology/mechanisms of resistance and susceptibility, including host genetics"], "article_id"=>481598, "categories"=>["Medicine", "Evolutionary Biology", "Cancer", "Plant Biology"], "users"=>["John Archer", "Andrew Rambaut", "Bruce E. Taillon", "P. Richard Harrigan", "Marilyn Lewis", "David L. Robertson"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1001022.g001", "stats"=>{"downloads"=>1, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_data_analysis_framework_/481598", "title"=>"The data analysis framework.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-12-16 00:26:38"}
  • {"files"=>["https://ndownloader.figshare.com/files/404994"], "description"=>"<div><p>Large-scale parallel pyrosequencing produces unprecedented quantities of sequence data. However, when generated from viral populations current mapping software is inadequate for dealing with the high levels of variation present, resulting in the potential for biased data loss. In order to apply the 454 Life Sciences' pyrosequencing system to the study of viral populations, we have developed software for the processing of highly variable sequence data. Here we demonstrate our software by analyzing two temporally sampled HIV-1 intra-patient datasets from a clinical study of maraviroc. This drug binds the CCR5 coreceptor, thus preventing HIV-1 infection of the cell. The objective is to determine viral tropism (CCR5 versus CXCR4 usage) and track the evolution of minority CXCR4-using variants that may limit the response to a maraviroc-containing treatment regimen. Five time points (two prior to treatment) were available from each patient. We first quantify the effects of divergence on initial read k-mer mapping and demonstrate the importance of utilizing population-specific template sequences in relation to the analysis of next-generation sequence data. Then, in conjunction with coreceptor prediction algorithms that infer HIV tropism, our software was used to quantify the viral population structure pre- and post-treatment. In both cases, low frequency CXCR4-using variants (2.5–15%) were detected prior to treatment. Following phylogenetic inference, these variants were observed to exist as distinct lineages that were maintained through time. Our analysis, thus confirms the role of pre-existing CXCR4-using virus in the emergence of maraviroc-insensitive HIV. The software will have utility for the study of intra-host viral diversity and evolution of other fast evolving viruses, and is available from <a href=\"http://www.bioinf.manchester.ac.uk/segminator/\">http://www.bioinf.manchester.ac.uk/segminator/</a>.</p></div>", "links"=>[], "tags"=>["evolutionary", "hiv-1", "cxcr4", "variants", "ultra-deep"], "article_id"=>140027, "categories"=>["Medicine", "Evolutionary Biology", "Cancer", "Cell Biology"], "users"=>["John Archer", "Andrew Rambaut", "Bruce E. Taillon", "P. Richard Harrigan", "Marilyn Lewis", "David L. Robertson"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1001022", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/The_Evolutionary_Analysis_of_Emerging_Low_Frequency_HIV_1_CXCR4_Using_Variants_through_Time_An_Ultra_Deep_Approach/140027", "title"=>"The Evolutionary Analysis of Emerging Low Frequency HIV-1 CXCR4 Using Variants through Time—An Ultra-Deep Approach", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2010-12-16 00:00:27"}
  • {"files"=>["https://ndownloader.figshare.com/files/811728"], "description"=>"<p>Predicted coreceptor usage, viral load, estimated proportion of population that is CXCR4-using (from % estimated by charge rule), number of V3 sequences extracted (in-frame) and CD4 cell count at different time points pre- and post-treatment for patient E.</p>", "links"=>[], "tags"=>["tropism"], "article_id"=>482092, "categories"=>["Medicine", "Evolutionary Biology", "Cancer", "Plant Biology"], "users"=>["John Archer", "Andrew Rambaut", "Bruce E. Taillon", "P. Richard Harrigan", "Marilyn Lewis", "David L. Robertson"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1001022.t004", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Patient_E_tropism_predictions_/482092", "title"=>"Patient E tropism predictions.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2010-12-16 00:34:52"}
  • {"files"=>["https://ndownloader.figshare.com/files/811879"], "description"=>"<p>Comparison of the number of reads extracted at each time point for patients D and E using k-mer mapping for a dataset-specific consensus and HXB2 templates. The genome coordinates 6900 to 7305 were used so as to include the V3 region and all reads spanning V3. The numbers in the first column are the total number of reads covering gp120.</p>", "links"=>[], "tags"=>["extraction"], "article_id"=>482247, "categories"=>["Medicine", "Evolutionary Biology", "Cancer", "Plant Biology"], "users"=>["John Archer", "Andrew Rambaut", "Bruce E. Taillon", "P. Richard Harrigan", "Marilyn Lewis", "David L. Robertson"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1001022.t001", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Read_extraction_comparison_/482247", "title"=>"Read extraction comparison.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2010-12-16 00:37:27"}
  • {"files"=>["https://ndownloader.figshare.com/files/811458"], "description"=>"<p>Each phylogeny shows the predicted R5 and CXCR4-using variants for the time points: screening, day 1, week 8, week 24 and week 30. See <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1001022#pcbi-1001022-g003\" target=\"_blank\">figure 3</a>'s legend for further details.</p>", "links"=>[], "tags"=>["relationships", "viral"], "article_id"=>481827, "categories"=>["Medicine", "Evolutionary Biology", "Cancer", "Plant Biology"], "users"=>["John Archer", "Andrew Rambaut", "Bruce E. Taillon", "P. Richard Harrigan", "Marilyn Lewis", "David L. Robertson"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1001022.g004", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Evolutionary_relationships_of_patient_E_s_viral_population_through_time_/481827", "title"=>"Evolutionary relationships of patient E's viral population through time.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-12-16 00:30:27"}
  • {"files"=>["https://ndownloader.figshare.com/files/811626"], "description"=>"<p>Frequency plots of PSSM scores of unique V3 sequences within each dataset. The red area indicates the region below the −6.96 threshold (R5), the green region indicates the area above the −2.88 threshold (CXCR4-using) and the grey area indicates the region between the two thresholds. The numbers within each plot area indicate the percentage of reads called as R5 or CXCR4-using for that region.</p>", "links"=>[], "tags"=>["computational biology/comparative sequence analysis", "computer science/applications", "evolutionary biology/bioinformatics", "infectious diseases/hiv infection and aids", "virology/mechanisms of resistance and susceptibility, including host genetics"], "article_id"=>481986, "categories"=>["Medicine", "Evolutionary Biology", "Cancer", "Plant Biology"], "users"=>["John Archer", "Andrew Rambaut", "Bruce E. Taillon", "P. Richard Harrigan", "Marilyn Lewis", "David L. Robertson"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1001022.g006", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Tropism_prediction_/481986", "title"=>"Tropism prediction.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-12-16 00:33:06"}
  • {"files"=>["https://ndownloader.figshare.com/files/811761"], "description"=>"<p>Comparison of use of a data-specific template with a published study which used HXB2 as a reference template <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1001022#pcbi.1001022-Tsibris1\" target=\"_blank\">[11]</a>. Dataset sizes are from Tsibris <i>et al.</i>, <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1001022#pcbi.1001022-Tsibris1\" target=\"_blank\">[11]</a>. The number of in-frame reads available for downstream analysis after correction based on a data-specific consensus is compared to the number of in-frame reads when no correction is applied.</p>", "links"=>[], "tags"=>["template"], "article_id"=>482126, "categories"=>["Medicine", "Evolutionary Biology", "Cancer", "Plant Biology"], "users"=>["John Archer", "Andrew Rambaut", "Bruce E. Taillon", "P. Richard Harrigan", "Marilyn Lewis", "David L. Robertson"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1001022.t005", "stats"=>{"downloads"=>1, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Reference_template_comparison_/482126", "title"=>"Reference template comparison.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2010-12-16 00:35:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/811565"], "description"=>"<p>Evolutionary tree inferred from all patient D's V3 nucleotide sequences (A), and all patient E's V3 nucleotide sequences (B). Colors (see key) indicate the frequency of each sequence. The scale bar represents nucleotide substitutions per site.</p>", "links"=>[], "tags"=>["hiv-1", "variants", "phylogenetic"], "article_id"=>481930, "categories"=>["Medicine", "Evolutionary Biology", "Cancer", "Plant Biology"], "users"=>["John Archer", "Andrew Rambaut", "Bruce E. Taillon", "P. Richard Harrigan", "Marilyn Lewis", "David L. Robertson"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1001022.g005", "stats"=>{"downloads"=>2, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Frequency_of_HIV_1_variants_in_the_phylogenetic_trees_/481930", "title"=>"Frequency of HIV-1 variants in the phylogenetic trees.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-12-16 00:32:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/811355"], "description"=>"<p>Each phylogeny shows the predicted R5 and CXCR4-using variants for the time points: screening, day 1, week 2, week 12 and week 16; only unique variants are shown. Subsequent to screening, the CXCR4-using variants from the previous time point are included for visualization purposes. Sequence logos for R5 and CXCR4-using sequences for each time point are also shown. Colors (see key) indicate sampling time in phylogenies and residue charges in sequence logos. The red numbers on the lineage separating branches at screening and day 1 indicate the branch support value from the <i>approximate likelihood ratio test</i> for the distinct CXCR4-using lineage present at these time points. The inset plots indicate the extent of the clustering present for these same lineages and time points (value next to circle on x axis) in comparison to a distribution of randomly assigned clusters; see methods for further details. The scale bar represents nucleotide substitutions per site.</p>", "links"=>[], "tags"=>["relationships", "viral"], "article_id"=>481719, "categories"=>["Medicine", "Evolutionary Biology", "Cancer", "Plant Biology"], "users"=>["John Archer", "Andrew Rambaut", "Bruce E. Taillon", "P. Richard Harrigan", "Marilyn Lewis", "David L. Robertson"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1001022.g003", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Evolutionary_relationships_of_patient_D_s_viral_population_through_time_/481719", "title"=>"Evolutionary relationships of patient D's viral population through time.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-12-16 00:28:39"}
  • {"files"=>["https://ndownloader.figshare.com/files/811805"], "description"=>"<p>The total number of reads completely spanning the V3 region (coordinates 7110 to 7217), regardless of the presence or absence of frame shift errors. The percentage containing singleton or dinucleotide insertion events across this region is displayed.</p>", "links"=>[], "tags"=>["computational biology/comparative sequence analysis", "computer science/applications", "evolutionary biology/bioinformatics", "infectious diseases/hiv infection and aids", "virology/mechanisms of resistance and susceptibility, including host genetics"], "article_id"=>482168, "categories"=>["Medicine", "Evolutionary Biology", "Cancer", "Plant Biology"], "users"=>["John Archer", "Andrew Rambaut", "Bruce E. Taillon", "P. Richard Harrigan", "Marilyn Lewis", "David L. Robertson"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1001022.t002", "stats"=>{"downloads"=>1, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_V3_region_coverage_/482168", "title"=>"V3 region coverage.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2010-12-16 00:36:08"}
  • {"files"=>["https://ndownloader.figshare.com/files/811844"], "description"=>"<p>Predicted coreceptor usage, viral load, estimated proportion of population that is CXCR4-using (from % estimated by charge rule), number of V3 sequences extracted (in-frame) and CD4 cell count at different time points pre- and post-treatment for patient D.</p>", "links"=>[], "tags"=>["tropism"], "article_id"=>482209, "categories"=>["Medicine", "Evolutionary Biology", "Cancer", "Plant Biology"], "users"=>["John Archer", "Andrew Rambaut", "Bruce E. Taillon", "P. Richard Harrigan", "Marilyn Lewis", "David L. Robertson"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1001022.t003", "stats"=>{"downloads"=>4, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Patient_D_tropism_predictions_/482209", "title"=>"Patient D tropism predictions.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2010-12-16 00:36:49"}

PMC Usage Stats | Further Information

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  • {"unique-ip"=>"15", "full-text"=>"10", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"10", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2012", "month"=>"10"}
  • {"unique-ip"=>"8", "full-text"=>"65", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2012", "month"=>"12"}
  • {"unique-ip"=>"8", "full-text"=>"9", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2013", "month"=>"1"}
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  • {"unique-ip"=>"6", "full-text"=>"6", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2013", "month"=>"5"}
  • {"unique-ip"=>"7", "full-text"=>"5", "pdf"=>"6", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"4", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2013", "month"=>"6"}
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  • {"unique-ip"=>"8", "full-text"=>"5", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"1", "cited-by"=>"14", "year"=>"2015", "month"=>"11"}
  • {"unique-ip"=>"10", "full-text"=>"6", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"8", "year"=>"2015", "month"=>"12"}
  • {"unique-ip"=>"11", "full-text"=>"12", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2016", "month"=>"1"}
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  • {"unique-ip"=>"3", "full-text"=>"4", "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"=>"5", "full-text"=>"4", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"9"}
  • {"unique-ip"=>"6", "full-text"=>"6", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"10"}
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  • {"unique-ip"=>"6", "full-text"=>"15", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"8"}
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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"=>"2018", "month"=>"2"}
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  • {"unique-ip"=>"4", "full-text"=>"3", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"5"}
  • {"unique-ip"=>"6", "full-text"=>"6", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"6"}
  • {"unique-ip"=>"7", "full-text"=>"4", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"7"}
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  • {"unique-ip"=>"2", "full-text"=>"5", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"9"}
  • {"unique-ip"=>"4", "full-text"=>"7", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"10"}
  • {"unique-ip"=>"7", "full-text"=>"8", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"12"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"11"}
  • {"unique-ip"=>"4", "full-text"=>"3", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"2", "year"=>"2019", "month"=>"2"}
  • {"unique-ip"=>"2", "full-text"=>"1", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"2", "year"=>"2019", "month"=>"3"}
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Relative Metric

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