ADaCGH: A Parallelized Web-Based Application and R Package for the Analysis of aCGH Data
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{"title"=>"ADaCGH: A parallelized web-based application and R package for the analysis of aCGH data", "type"=>"journal", "authors"=>[{"first_name"=>"Ramón", "last_name"=>"Díaz-Uriarte", "scopus_author_id"=>"6603594977"}, {"first_name"=>"Oscar M.", "last_name"=>"Rueda", "scopus_author_id"=>"16686675000"}], "year"=>2007, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "pui"=>"351338875", "doi"=>"10.1371/journal.pone.0000737", "sgr"=>"40349108567", "scopus"=>"2-s2.0-40349108567", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "pmid"=>"17710137"}, "id"=>"d9b8c94d-a270-3b75-98df-8cf4f65c09b8", "abstract"=>"BACKGROUND: Copy number alterations (CNAs) in genomic DNA have been associated with complex human diseases, including cancer. One of the most common techniques to detect CNAs is array-based comparative genomic hybridization (aCGH). The availability of aCGH platforms and the need for identification of CNAs has resulted in a wealth of methodological studies.\\n\\nMETHODOLOGY/PRINCIPAL FINDINGS: ADaCGH is an R package and a web-based application for the analysis of aCGH data. It implements eight methods for detection of CNAs, gains and losses of genomic DNA, including all of the best performing ones from two recent reviews (CBS, GLAD, CGHseg, HMM). For improved speed, we use parallel computing (via MPI). Additional information (GO terms, PubMed citations, KEGG and Reactome pathways) is available for individual genes, and for sets of genes with altered copy numbers.\\n\\nCONCLUSIONS/SIGNIFICANCE: ADACGH represents a qualitative increase in the standards of these types of applications: a) all of the best performing algorithms are included, not just one or two; b) we do not limit ourselves to providing a thin layer of CGI on top of existing BioConductor packages, but instead carefully use parallelization, examining different schemes, and are able to achieve significant decreases in user waiting time (factors up to 45x); c) we have added functionality not currently available in some methods, to adapt to recent recommendations (e.g., merging of segmentation results in wavelet-based and CGHseg algorithms); d) we incorporate redundancy, fault-tolerance and checkpointing, which are unique among web-based, parallelized applications; e) all of the code is available under open source licenses, allowing to build upon, copy, and adapt our code for other software projects.", "link"=>"http://www.mendeley.com/research/adacgh-parallelized-webbased-application-r-package-analysis-acgh-data", "reader_count"=>38, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>6, "Researcher"=>12, "Student > Ph. D. Student"=>10, "Student > Postgraduate"=>2, "Other"=>3, "Student > Master"=>4, "Professor"=>1}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>6, "Researcher"=>12, "Student > Ph. D. Student"=>10, "Student > Postgraduate"=>2, "Other"=>3, "Student > Master"=>4, "Professor"=>1}, "reader_count_by_subject_area"=>{"Biochemistry, Genetics and Molecular Biology"=>6, "Mathematics"=>1, "Agricultural and Biological Sciences"=>24, "Medicine and Dentistry"=>5, "Computer Science"=>2}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>5}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>24}, "Computer Science"=>{"Computer Science"=>2}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>6}, "Mathematics"=>{"Mathematics"=>1}}, "reader_count_by_country"=>{"Canada"=>1, "Belgium"=>1, "United States"=>1, "Japan"=>1, "Egypt"=>1, "Chile"=>1, "Australia"=>1}, "group_count"=>5}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/946539"], "description"=>"<p>Black: execution flow. Gray: read (←) or write (→) to/from files/nodes/hardware elements.</p>", "links"=>[], "tags"=>["mechanisms"], "article_id"=>616900, "categories"=>["Genetics", "Mathematics", "Infectious Diseases", "Cancer"], "users"=>["Ramón Díaz-Uriarte", "Oscar M. Rueda"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0000737.g005", "stats"=>{"downloads"=>2, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Flow_of_information_between_application_components_main_mechanisms_for_crash_recovery_and_fault_tolerance_/616900", "title"=>"Flow of information between application components: main mechanisms for crash recovery and fault tolerance.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 12:05:34"}
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  • {"files"=>["https://ndownloader.figshare.com/files/946394"], "description"=>"<p>User wall time of the R code using parallelization over arrays by chromosomes or over array (all methods shown, except ACE) or chromosome (ACE). “Slaves: 2” or “Slaves: 4” indicates the number of slaves per node. The two timings shown were obtained from an otherwise idle cluster, with hardware and software as in previous figures.</p>", "links"=>[], "tags"=>["parallelization"], "article_id"=>616763, "categories"=>["Genetics", "Mathematics", "Infectious Diseases", "Cancer"], "users"=>["Ramón Díaz-Uriarte", "Oscar M. Rueda"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0000737.g003", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparing_parallelization_schemes_/616763", "title"=>"Comparing parallelization schemes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 12:04:18"}
  • {"files"=>["https://ndownloader.figshare.com/files/946466"], "description"=>"<p>Overview of the flow of information between the main components of the web-based application.</p>", "links"=>[], "tags"=>["components", "web-based"], "article_id"=>616828, "categories"=>["Genetics", "Mathematics", "Infectious Diseases", "Cancer"], "users"=>["Ramón Díaz-Uriarte", "Oscar M. Rueda"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0000737.g004", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Overview_of_the_flow_of_information_between_the_main_components_of_the_web_based_application_/616828", "title"=>"Overview of the flow of information between the main components of the web-based application.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 12:05:13"}
  • {"files"=>["https://ndownloader.figshare.com/files/946199"], "description"=>"<p>Values shown are the mean of four replicates, obtained in an otherwise idle cluster with 30 nodes, each with two dual-core AMD Opteron 2.2 GHz CPUs and 6 GB RAM, running Debian GNU/Linux and a stock 2.6.8 kernel, with version 7.1.2 of LAM/MPI and version 2.1.4 (patched) of R. Numbers next to the lines (60, 30, 10) indicate the total number of Rslaves in the cluster (2 slaves per node, and a maximum of 30 nodes used).</p>", "links"=>[], "tags"=>["parallelization"], "article_id"=>616567, "categories"=>["Genetics", "Mathematics", "Infectious Diseases", "Cancer"], "users"=>["Ramón Díaz-Uriarte", "Oscar M. Rueda"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0000737.g001", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Effects_of_parallelization_of_the_R_code_on_the_user_wall_time_for_several_methods_/616567", "title"=>"Effects of parallelization of the R code on the user wall time for several methods.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 12:03:12"}

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  • {"unique-ip"=>"4", "full-text"=>"3", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"9"}
  • {"unique-ip"=>"5", "full-text"=>"6", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"10"}

Relative Metric

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