Performance and Scalability of Discriminative Metrics for Comparative Gene Identification in 12 Drosophila Genomes
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{"title"=>"Performance and scalability of discriminative metrics for comparative gene identification in 12 Drosophila genomes", "type"=>"journal", "authors"=>[{"first_name"=>"Michael F.", "last_name"=>"Lin", "scopus_author_id"=>"35278604000"}, {"first_name"=>"Ameya N.", "last_name"=>"Deoras", "scopus_author_id"=>"6507547732"}, {"first_name"=>"Matthew D.", "last_name"=>"Rasmussen", "scopus_author_id"=>"22980672500"}, {"first_name"=>"Manolis", "last_name"=>"Kellis", "scopus_author_id"=>"6602385400"}], "year"=>2008, "source"=>"PLoS Computational Biology", "identifiers"=>{"isbn"=>"1553-7358 (Electronic)\\n1553-734X (Linking)", "pmid"=>"18421375", "pui"=>"351656717", "issn"=>"1553734X", "scopus"=>"2-s2.0-43249097469", "sgr"=>"43249097469", "doi"=>"10.1371/journal.pcbi.1000067"}, "id"=>"a0e63db1-feb5-36db-befb-07fb1680ffaf", "abstract"=>"Comparative genomics of multiple related species is a powerful methodology for the discovery of functional genomic elements, and its power should increase with the number of species compared. Here, we use 12 Drosophila genomes to study the power of comparative genomics metrics to distinguish between protein-coding and non-coding regions. First, we study the relative power of different comparative metrics and their relationship to single-species metrics. We find that even relatively simple multi-species metrics robustly outperform advanced single-species metrics, especially for shorter exons (< or =240 nt), which are common in animal genomes. Moreover, the two capture largely independent features of protein-coding genes, with different sensitivity/specificity trade-offs, such that their combinations lead to even greater discriminatory power. In addition, we study how discovery power scales with the number and phylogenetic distance of the genomes compared. We find that species at a broad range of distances are comparably effective informants for pairwise comparative gene identification, but that these are surpassed by multi-species comparisons at similar evolutionary divergence. In particular, while pairwise discovery power plateaued at larger distances and never outperformed the most advanced single-species metrics, multi-species comparisons continued to benefit even from the most distant species with no apparent saturation. Last, we find that genes in functional categories typically considered fast-evolving can nonetheless be recovered at very high rates using comparative methods. Our results have implications for comparative genomics analyses in any species, including the human.", "link"=>"http://www.mendeley.com/research/performance-scalability-discriminative-metrics-comparative-gene-identification-12-drosophila-genomes", "reader_count"=>56, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>8, "Researcher"=>16, "Student > Ph. D. Student"=>20, "Student > Postgraduate"=>2, "Student > Master"=>1, "Other"=>1, "Student > Bachelor"=>2, "Professor"=>6}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>8, "Researcher"=>16, "Student > Ph. D. Student"=>20, "Student > Postgraduate"=>2, "Student > Master"=>1, "Other"=>1, "Student > Bachelor"=>2, "Professor"=>6}, "reader_count_by_subject_area"=>{"Engineering"=>1, "Biochemistry, Genetics and Molecular Biology"=>7, "Mathematics"=>2, "Agricultural and Biological Sciences"=>41, "Medicine and Dentistry"=>1, "Computer Science"=>4}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>41}, "Computer Science"=>{"Computer Science"=>4}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>7}, "Mathematics"=>{"Mathematics"=>2}}, "reader_count_by_country"=>{"Netherlands"=>1, "United States"=>6, "China"=>1, "Ireland"=>1, "Denmark"=>1, "United Kingdom"=>1, "Germany"=>1}, "group_count"=>3}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/933383"], "description"=>"<p>(A) ROC curves for <i>K<sub>A</sub></i>/<i>K<sub>S</sub></i> using <i>D. melanogaster</i> with each of five different informant species. Species at a wide range of evolutionary distances performed comparably, except for <i>D. erecta</i>, the most closely related to <i>D. melanogaster</i>, which clearly underperformed the others. (B) MAE and AAC error statistics for each pairwise comparative metrics applied to the same five informants. <i>D. ananassae</i> (blue) is overall the preferred informant, but not uniformly so. For TBLASTX, the performance is also shown using mosquito (<i>Anopheles gambiae</i>) and honeybee (<i>Apis mellifera</i>), which led to worse performance than the <i>Drosophila</i> species. No pairwise comparison outperformed the best single-sequence metric (Z curve).</p>", "links"=>[], "tags"=>["informant"], "article_id"=>603834, "categories"=>["Medicine", "Infectious Diseases"], "users"=>["Michael F. Lin", "Ameya N. Deoras", "Matthew D. Rasmussen", "Manolis Kellis"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000067.g004", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Pairwise_discovery_power_using_different_informant_species_/603834", "title"=>"Pairwise discovery power using different informant species.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-04-18 01:03:54"}
  • {"files"=>["https://ndownloader.figshare.com/files/933522"], "description"=>"<p>Additional details are provided in <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000067#s4\" target=\"_blank\">Methods</a>.</p>", "links"=>[], "tags"=>["metrics"], "article_id"=>603976, "categories"=>["Medicine", "Infectious Diseases"], "users"=>["Michael F. Lin", "Ameya N. Deoras", "Matthew D. Rasmussen", "Manolis Kellis"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000067.t001", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Discriminative_metrics_for_gene_identification_/603976", "title"=>"Discriminative metrics for gene identification.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2008-04-18 01:06:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/933206"], "description"=>"<p>(A) Multidimensional scaling (MDS) visualization in which each point represents a metric and the distance between any two points approximately represents their dissimilarity, measured as 1-(rank correlation of the scores of the known exons). Hybrid metrics appear closer to the center, suggesting that they successfully combine distinct information from the individual metrics. (B) ROC curves showing the performance of two hybrid metrics created by combining five comparative and single-sequence metrics using Linear Discriminant Analysis (LDA) or a Support Vector Machine (SVM). The hybrid metrics outperformed all of their input metrics.</p>", "links"=>[], "tags"=>["metrics", "metric"], "article_id"=>603654, "categories"=>["Medicine", "Infectious Diseases"], "users"=>["Michael F. Lin", "Ameya N. Deoras", "Matthew D. Rasmussen", "Manolis Kellis"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000067.g002", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Independence_of_metrics_and_discovery_power_of_metric_combinations_/603654", "title"=>"Independence of metrics and discovery power of metric combinations.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-04-18 01:00:54"}
  • {"files"=>["https://ndownloader.figshare.com/files/933460"], "description"=>"<p>(A) ROC curves for the <i>dN/dS</i> test using subsets of <i>Drosophila</i> species corresponding to increasingly broad phylogenetic clades from <i>D. melanogaster</i> (see <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000067#pcbi-1000067-g001\" target=\"_blank\">Figure 1</a>). Discriminatory power steadily increased as more informants were used, leading to strictly better sensitivity and specificity. (B) Effect of additional species was most pronounced for short exon lengths. (<i>x</i>-axis) mean length within a quantile of the sequence length distribution (<i>y</i>-axis) sensitivity of the <i>dN</i>/<i>dS</i> test within each quantile at fixed specificity (99%). (C) MAE and AAC error statistics for each multi-species comparative metric using the same subsets of informants. Also shown for comparison are the best pairwise analysis and the best single-sequence metric, both of which are outperformed by multi-species methods with sufficient informants.</p>", "links"=>[], "tags"=>["numbers", "informant"], "article_id"=>603906, "categories"=>["Medicine", "Infectious Diseases"], "users"=>["Michael F. Lin", "Ameya N. Deoras", "Matthew D. Rasmussen", "Manolis Kellis"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000067.g005", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Multi_species_discovery_power_using_increasing_numbers_of_informant_species_/603906", "title"=>"Multi-species discovery power using increasing numbers of informant species.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-04-18 01:05:06"}
  • {"files"=>["https://ndownloader.figshare.com/files/933313"], "description"=>"<p>(A) Phylogenetic tree and estimated neutral branch lengths for the species. Tree topology follows the accepted phylogeny of these species <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000067#pcbi.1000067-Drosophila1\" target=\"_blank\">[21]</a>,<a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000067#pcbi.1000067-Stark1\" target=\"_blank\">[22]</a>. Neutral substitution rates estimated from 12,861 4-fold degenerate sites in syntenic one-to-one orthologs (see <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000067#s4\" target=\"_blank\">Methods</a>). (B) Pairwise distance of each of the 11 other <i>Drosophila</i> species from <i>D. melanogaster</i>, as compared to similarly estimated distances for vertebrates. (C) Total independent branch length provided by several subsets of the <i>Drosophila</i> species used to benchmark multi-species methods.</p>", "links"=>[], "tags"=>["distances", "relating", "12"], "article_id"=>603760, "categories"=>["Medicine", "Infectious Diseases"], "users"=>["Michael F. Lin", "Ameya N. Deoras", "Matthew D. Rasmussen", "Manolis Kellis"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000067.g003", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Evolutionary_distances_relating_12_Drosophila_species_/603760", "title"=>"Evolutionary distances relating 12 <i>Drosophila</i> species.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-04-18 01:02:40"}
  • {"files"=>["https://ndownloader.figshare.com/files/459924", "https://ndownloader.figshare.com/files/459930", "https://ndownloader.figshare.com/files/459938", "https://ndownloader.figshare.com/files/459949", "https://ndownloader.figshare.com/files/459958", "https://ndownloader.figshare.com/files/459973"], "description"=>"<div><p>Comparative genomics of multiple related species is a powerful methodology for the discovery of functional genomic elements, and its power should increase with the number of species compared. Here, we use 12 <em>Drosophila</em> genomes to study the power of comparative genomics metrics to distinguish between protein-coding and non-coding regions. First, we study the relative power of different comparative metrics and their relationship to single-species metrics. We find that even relatively simple multi-species metrics robustly outperform advanced single-species metrics, especially for shorter exons (≤240 nt), which are common in animal genomes. Moreover, the two capture largely independent features of protein-coding genes, with different sensitivity/specificity trade-offs, such that their combinations lead to even greater discriminatory power. In addition, we study how discovery power scales with the number and phylogenetic distance of the genomes compared. We find that species at a broad range of distances are comparably effective informants for pairwise comparative gene identification, but that these are surpassed by multi-species comparisons at similar evolutionary divergence. In particular, while pairwise discovery power plateaued at larger distances and never outperformed the most advanced single-species metrics, multi-species comparisons continued to benefit even from the most distant species with no apparent saturation. Last, we find that genes in functional categories typically considered fast-evolving can nonetheless be recovered at very high rates using comparative methods. Our results have implications for comparative genomics analyses in any species, including the human.</p></div>", "links"=>[], "tags"=>["scalability", "discriminative", "metrics", "comparative", "12", "genomes"], "article_id"=>150615, "categories"=>["Medicine", "Cancer"], "users"=>["Michael F. Lin", "Ameya N. Deoras", "Matthew D. Rasmussen", "Manolis Kellis"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1000067.s001", "https://dx.doi.org/10.1371/journal.pcbi.1000067.s002", "https://dx.doi.org/10.1371/journal.pcbi.1000067.s003", "https://dx.doi.org/10.1371/journal.pcbi.1000067.s004", "https://dx.doi.org/10.1371/journal.pcbi.1000067.s005", "https://dx.doi.org/10.1371/journal.pcbi.1000067.s006"], "stats"=>{"downloads"=>15, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Performance_and_Scalability_of_Discriminative_Metrics_for_Comparative_Gene_Identification_in_12_Drosophila_Genomes/150615", "title"=>"Performance and Scalability of Discriminative Metrics for Comparative Gene Identification in 12 <em>Drosophila</em> Genomes", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2008-04-18 00:10:15"}
  • {"files"=>["https://ndownloader.figshare.com/files/933097"], "description"=>"<p>(A) ROC curves showing sensitivity and specificity of each metric on classifying 10,722 known exons and 39,181 random non-coding regions. Comparative methods tended to outperform single-sequence metrics, with the exception of a baseline sequence conservation metric. CSF and the <i>dN</i>/<i>dS</i> test achieved near-perfect specificity, while RFC achieved high sensitivity. (B) Summary error statistics for each metric computed from the ROC curves. Minimum Average Error (MAE) is the minimum average of the false negative rate and false positive rate. Area Above the Curve (AAC) is the area above the ROC curve in the unit square. (C) MAE and AAC error statistics for each metric when the dataset is partitioned into several sequence length categories. All metrics tended to perform better on longer sequences than on shorter sequences. Comparative methods strongly outperformed single-sequence metrics on short sequences (60–240 nt). Inset: relative size of each sequence length category.</p>", "links"=>[], "tags"=>["discriminative", "metrics", "12"], "article_id"=>603542, "categories"=>["Medicine", "Infectious Diseases"], "users"=>["Michael F. Lin", "Ameya N. Deoras", "Matthew D. Rasmussen", "Manolis Kellis"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000067.g001", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Overall_discovery_power_of_discriminative_metrics_using_12_genomes_/603542", "title"=>"Overall discovery power of discriminative metrics using 12 genomes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-04-18 00:59:02"}

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