Functional-Network-Based Gene Set Analysis Using Gene-Ontology
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{"title"=>"Functional-Network-Based Gene Set Analysis Using Gene-Ontology", "type"=>"journal", "authors"=>[{"first_name"=>"Billy", "last_name"=>"Chang", "scopus_author_id"=>"57191484666"}, {"first_name"=>"Rafal", "last_name"=>"Kustra", "scopus_author_id"=>"6602442374"}, {"first_name"=>"Weidong", "last_name"=>"Tian", "scopus_author_id"=>"56937642800"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"sgr"=>"84873931278", "doi"=>"10.1371/journal.pone.0055635", "issn"=>"19326203", "pui"=>"368342470", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "pmid"=>"23418449", "scopus"=>"2-s2.0-84873931278"}, "id"=>"3785c52e-b7d5-36d8-b0c8-43ac5f3f70f2", "abstract"=>"To account for the functional non-equivalence among a set of genes within a biological pathway when performing gene set analysis, we introduce GOGANPA, a network-based gene set analysis method, which up-weights genes with functions relevant to the gene set of interest. The genes are weighted according to its degree within a genome-scale functional network constructed using the functional annotations available from the gene ontology database. By benchmarking GOGANPA using a well-studied P53 data set and three breast cancer data sets, we will demonstrate the power and reproducibility of our proposed method over traditional unweighted approaches and a competing network-based approach that involves a complex integrated network. GOGANPA’s sole reliance on gene ontology further allows GOGANPA to be widely applicable to the analysis of any gene-ontology-annotated genome.", "link"=>"http://www.mendeley.com/research/functionalnetworkbased-gene-set-analysis-using-geneontology-1", "reader_count"=>37, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>5, "Researcher"=>14, "Student > Ph. D. Student"=>8, "Student > Postgraduate"=>1, "Student > Master"=>5, "Other"=>2, "Professor"=>2}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>5, "Researcher"=>14, "Student > Ph. D. Student"=>8, "Student > Postgraduate"=>1, "Student > Master"=>5, "Other"=>2, "Professor"=>2}, "reader_count_by_subject_area"=>{"Unspecified"=>1, "Engineering"=>2, "Environmental Science"=>1, "Biochemistry, Genetics and Molecular Biology"=>6, "Agricultural and Biological Sciences"=>19, "Neuroscience"=>1, "Psychology"=>1, "Computer Science"=>6}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>2}, "Neuroscience"=>{"Neuroscience"=>1}, "Psychology"=>{"Psychology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>19}, "Computer Science"=>{"Computer Science"=>6}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>6}, "Unspecified"=>{"Unspecified"=>1}, "Environmental Science"=>{"Environmental Science"=>1}}, "reader_count_by_country"=>{"South Korea"=>1, "Netherlands"=>1, "United States"=>3, "South Africa"=>1, "Slovenia"=>1}, "group_count"=>1}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/489504"], "description"=>"<p>The pathways’ scores and rankings (in brackets) as scored and ranked by the four GSA methods are presented. All pathways presented have -value , and have ranked within top 10 by at least one of the methods being compared. Abbreviations: carbohydrates: metabolism of carbohydrates; pyruvate: pyruvate metabolism and TCA cycle; basigin: basigin interactions; telomere ends: packaging of telomere ends; glycosaminoglycan: glycosaminoglycan degradation; bile acids/salts: metabolism of bile acids and bile salts; glycolysis gluc.: glycolysis gluconeogenesis; ARVC: arrhythmogenic right ventricular cardiomyopathy arvc.</p>", "links"=>[], "tags"=>["genetics and genomics", "Computational biology", "mathematics"], "article_id"=>160033, "categories"=>["Mathematics", "Biological Sciences", "Genetics"], "users"=>["Billy Chang", "Rafal Kustra", "Weidong Tian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0055635.t003", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Asthma_Data_8211_Results_/160033", "title"=>"Asthma Data – Results.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-13 00:00:33"}
  • {"files"=>["https://ndownloader.figshare.com/files/489312"], "description"=>"<p>See caption of <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055635#pone-0055635-g004\" target=\"_blank\">Figure 4</a> for descriptions. (A) The GANPA network. (B) The GOGANPA network.</p>", "links"=>[], "tags"=>["vegf"], "article_id"=>159842, "categories"=>["Mathematics", "Biological Sciences", "Genetics"], "users"=>["Billy Chang", "Rafal Kustra", "Weidong Tian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0055635.g007", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Asthma_Data_VEGF_Pathway_/159842", "title"=>"Asthma Data: VEGF Pathway.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-13 02:44:02"}
  • {"files"=>["https://ndownloader.figshare.com/files/489472"], "description"=>"<p>Pathways with normalized test-statistics ranked above 80 in all three data sets by at least one method are listed. The rankings of the pathway obtained from the three breast cancer data sets are recorded. Rankings above 80 across all three data sets are boldfaced. GOGANPA has identified the most number of conserved pathways across the three data sets. Abbreviation: syn. di/tri-phosph.: synthesis and interconversion of nucleotide di and triphosphates; metabolism nts.: metablism of nucleotides; aldo. reg. Na. reabs.: aldosterone regulated sodium reabsorption; APC: regulation of APC/C activators between G1/S and early anaphase; reg. actin cyto.: regulation of actin cytoskeleton; down strm. sig. trans.: down stream signal transduction; CDC20: Cdc20 Phospho-APC/C mediated degradation of Cyclin A.</p>", "links"=>[], "tags"=>["cancer"], "article_id"=>160003, "categories"=>["Mathematics", "Biological Sciences", "Genetics"], "users"=>["Billy Chang", "Rafal Kustra", "Weidong Tian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0055635.t002", "stats"=>{"downloads"=>5, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Breast_Cancer_Data_8211_Results_/160003", "title"=>"Breast Cancer Data – Results.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-13 00:00:03"}
  • {"files"=>["https://ndownloader.figshare.com/files/488845"], "description"=>"<p>GOGANPA transforms a GO similarity matrix into a gene network. Gene weights are then evaluated for each pathway (represented by transparent coloured boxes), and the weights are integrated into the gene expression data to evaluate the test statistics and weighted pathway test statistics.</p>", "links"=>[], "tags"=>["genetics and genomics", "Computational biology", "mathematics"], "article_id"=>159370, "categories"=>["Mathematics", "Biological Sciences", "Genetics"], "users"=>["Billy Chang", "Rafal Kustra", "Weidong Tian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0055635.g001", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Overview_of_GOGANPA_/159370", "title"=>"Overview of GOGANPA.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-13 02:36:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/488941"], "description"=>"<p>Node sizes correspond to the gene weights evaluated by GOGANPA. The functional-centrality of the <i>TP53</i> gene is highlighted by being assigned a high weight. The <i>CDKN1A</i> gene, a gene responsible for cell-cycle regulation and DNA-damage response, also receives a high weight due to its functional significance within the P53 Pathway.</p>", "links"=>[], "tags"=>["genetics and genomics", "Computational biology", "mathematics"], "article_id"=>159468, "categories"=>["Mathematics", "Biological Sciences", "Genetics"], "users"=>["Billy Chang", "Rafal Kustra", "Weidong Tian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0055635.g002", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_P53_Pathway_/159468", "title"=>"P53 Pathway.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-13 02:37:48"}
  • {"files"=>["https://ndownloader.figshare.com/files/489133"], "description"=>"<p>See caption of <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055635#pone-0055635-g004\" target=\"_blank\">Figure 4</a> for descriptions. The highly differentially expressed <i>BAX</i> gene, considered less important by GANPA (A), has been strongly up-weighted by GOGANPA (B), allowing GOGANPA to discover the ceramide pathway’s significance.</p>", "links"=>[], "tags"=>["ceramide"], "article_id"=>159661, "categories"=>["Mathematics", "Biological Sciences", "Genetics"], "users"=>["Billy Chang", "Rafal Kustra", "Weidong Tian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0055635.g005", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_p53_Data_Ceramide_Pathway_/159661", "title"=>"p53 Data - Ceramide Pathway.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-13 02:41:01"}
  • {"files"=>["https://ndownloader.figshare.com/files/489205"], "description"=>"<p>See caption of <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055635#pone-0055635-g004\" target=\"_blank\">Figure 4</a> for descriptions. (A) In GANPA, a huge amount of co-expressing genes-pairs form a strongly connected network, and GANPA cannot distinguish the highly differential genes from the other less differentially expressed genes. (B) GOGANPA, on the other hand, only considers functional relationships, and hence provides a much sparser network that highlights the importance of the highly differentially expressed <i>UBE2C</i> and <i>CDK1</i> genes.</p>", "links"=>[], "tags"=>["cancer", "cdc20"], "article_id"=>159733, "categories"=>["Mathematics", "Biological Sciences", "Genetics"], "users"=>["Billy Chang", "Rafal Kustra", "Weidong Tian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0055635.g006", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Breast_Cancer_Data_CDC20_Pathway_/159733", "title"=>"Breast Cancer Data: CDC20 Pathway.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-13 02:42:13"}
  • {"files"=>["https://ndownloader.figshare.com/files/489072"], "description"=>"<p>Deeper colour represents stronger differential expression (i.e. higher ). Grey nodes represent genes with missing expression measurements. Node sizes correspond to the gene weights evaluated by GANPA (A) and GOGANPA (B). Comparing to GANPA, while GOGANPA has down-weighted the differentially expressed <i>BCL2</i> gene and <i>MAPKAPK2</i> gene, it has up-weighted the differentially expressed <i>FAS, TNF</i>, and <i>IL1A</i> genes, and has hence produced a higher pathway test statistic and a smaller -value for the HSP27 Pathway.</p>", "links"=>[], "tags"=>["hsp27"], "article_id"=>159606, "categories"=>["Mathematics", "Biological Sciences", "Genetics"], "users"=>["Billy Chang", "Rafal Kustra", "Weidong Tian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0055635.g004", "stats"=>{"downloads"=>2, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_p53_Data_HSP27_Pathway_/159606", "title"=>"p53 Data - HSP27 Pathway.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-13 02:40:06"}
  • {"files"=>["https://ndownloader.figshare.com/files/489371"], "description"=>"<p>See caption of <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055635#pone-0055635-g004\" target=\"_blank\">Figure 4</a> for descriptions. (A) The GANPA network. (B) The GOGANPA network.</p>", "links"=>[], "tags"=>["basigin"], "article_id"=>159898, "categories"=>["Mathematics", "Biological Sciences", "Genetics"], "users"=>["Billy Chang", "Rafal Kustra", "Weidong Tian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0055635.g008", "stats"=>{"downloads"=>1, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Asthma_Data_Basigin_Interaction_Pathway_/159898", "title"=>"Asthma Data: Basigin Interaction Pathway.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-13 02:44:58"}
  • {"files"=>["https://ndownloader.figshare.com/files/485038", "https://ndownloader.figshare.com/files/485040", "https://ndownloader.figshare.com/files/485044"], "description"=>"<div><p>To account for the functional non-equivalence among a set of genes within a biological pathway when performing gene set analysis, we introduce GOGANPA, a network-based gene set analysis method, which up-weights genes with functions relevant to the gene set of interest. The genes are weighted according to its degree within a genome-scale functional network constructed using the functional annotations available from the gene ontology database. By benchmarking GOGANPA using a well-studied P53 data set and three breast cancer data sets, we will demonstrate the power and reproducibility of our proposed method over traditional unweighted approaches and a competing network-based approach that involves a complex integrated network. GOGANPA’s sole reliance on gene ontology further allows GOGANPA to be widely applicable to the analysis of any gene-ontology-annotated genome.</p> </div>", "links"=>[], "tags"=>["functional-network-based", "gene-ontology"], "article_id"=>156735, "categories"=>["Mathematics", "Biological Sciences", "Genetics"], "users"=>["Billy Chang", "Rafal Kustra", "Weidong Tian"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0055635.s001", "https://dx.doi.org/10.1371/journal.pone.0055635.s002", "https://dx.doi.org/10.1371/journal.pone.0055635.s003"], "stats"=>{"downloads"=>16, "page_views"=>50, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Functional_Network_Based_Gene_Set_Analysis_Using_Gene_Ontology__/156735", "title"=>"Functional-Network-Based Gene Set Analysis Using Gene-Ontology", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2013-02-13 01:52:15"}
  • {"files"=>["https://ndownloader.figshare.com/files/489023"], "description"=>"<p>(A) The gene-of-interest (yellow node) is connected to certain single-protein-coding genes and two groups of MSP-coding genes (inside blue shades). The presence of MSP-coding genes inflates both and for the gene-of-interest inside the pathway shaded in yellow. (B) Upon collapsing the MSP-coding gene groups into single units, both and are reduced at the protein level.</p>", "links"=>[], "tags"=>["genetics and genomics", "Computational biology", "mathematics"], "article_id"=>159548, "categories"=>["Mathematics", "Biological Sciences", "Genetics"], "users"=>["Billy Chang", "Rafal Kustra", "Weidong Tian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0055635.g003", "stats"=>{"downloads"=>2, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Illustrating_MSP_correction_/159548", "title"=>"Illustrating MSP-correction.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-13 02:39:08"}
  • {"files"=>["https://ndownloader.figshare.com/files/489437"], "description"=>"<p>Controlling FDR at 0.15, the -values obtained by each method for the pathways deemed significant by at least one of the five methods are listed, with -values 0.15 boldfaced. The absM method can only identify six pathways, while GANPA can identify four more. Compared to GANPA, GOGANPA can discover six more pathways, while discovering all the pathways deemed significant by GANPA. Abbreviation: st dictyostelium: st dictyostelium discoideum camp chemotaxis pathway.</p>", "links"=>[], "tags"=>["genetics and genomics", "Computational biology", "mathematics"], "article_id"=>159967, "categories"=>["Mathematics", "Biological Sciences", "Genetics"], "users"=>["Billy Chang", "Rafal Kustra", "Weidong Tian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0055635.t001", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_p53_Data_8211_Results_/159967", "title"=>"p53 Data – Results.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-13 02:46:07"}

PMC Usage Stats | Further Information

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Relative Metric

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