PIIKA 2: An Expanded, Web-Based Platform for Analysis of Kinome Microarray Data
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{"title"=>"PIIKA 2: An expanded, web-based platform for analysis of kinome microarray data", "type"=>"journal", "authors"=>[{"first_name"=>"Brett", "last_name"=>"Trost", "scopus_author_id"=>"35485738000"}, {"first_name"=>"Jason", "last_name"=>"Kindrachuk", "scopus_author_id"=>"6507134040"}, {"first_name"=>"Pekka", "last_name"=>"Määttänen", "scopus_author_id"=>"14058672100"}, {"first_name"=>"Scott", "last_name"=>"Napper", "scopus_author_id"=>"7003628577"}, {"first_name"=>"Anthony", "last_name"=>"Kusalik", "scopus_author_id"=>"6603155105"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"pmid"=>"24312246", "doi"=>"10.1371/journal.pone.0080837", "sgr"=>"84896708262", "scopus"=>"2-s2.0-84896708262", "issn"=>"19326203", "pui"=>"372438478"}, "id"=>"93f789db-2020-390f-b4c8-b330f32660f3", "abstract"=>"Kinome microarrays are comprised of peptides that act as phosphorylation targets for protein kinases. This platform is growing in popularity due to its ability to measure phosphorylation-mediated cellular signaling in a high-throughput manner. While software for analyzing data from DNA microarrays has also been used for kinome arrays, differences between the two technologies and associated biologies previously led us to develop Platform for Intelligent, Integrated Kinome Analysis (PIIKA), a software tool customized for the analysis of data from kinome arrays. Here, we report the development of PIIKA 2, a significantly improved version with new features and improvements in the areas of clustering, statistical analysis, and data visualization. Among other additions to the original PIIKA, PIIKA 2 now allows the user to: evaluate statistically how well groups of samples cluster together; identify sets of peptides that have consistent phosphorylation patterns among groups of samples; perform hierarchical clustering analysis with bootstrapping; view false negative probabilities and positive and negative predictive values for t-tests between pairs of samples; easily assess experimental reproducibility; and visualize the data using volcano plots, scatterplots, and interactive three-dimensional principal component analyses. Also new in PIIKA 2 is a web-based interface, which allows users unfamiliar with command-line tools to easily provide input and download the results. Collectively, the additions and improvements described here enhance both the breadth and depth of analyses available, simplify the user interface, and make the software an even more valuable tool for the analysis of kinome microarray data. Both the web-based and stand-alone versions of PIIKA 2 can be accessed via http://saphire.usask.ca.", "link"=>"http://www.mendeley.com/research/piika-2-expanded-webbased-platform-analysis-kinome-microarray-data", "reader_count"=>7, "reader_count_by_academic_status"=>{"Student > Doctoral Student"=>1, "Researcher"=>4, "Student > Master"=>1, "Student > Bachelor"=>1}, "reader_count_by_user_role"=>{"Student > Doctoral Student"=>1, "Researcher"=>4, "Student > Master"=>1, "Student > Bachelor"=>1}, "reader_count_by_subject_area"=>{"Agricultural and Biological Sciences"=>4, "Computer Science"=>1, "Immunology and Microbiology"=>1, "Biochemistry, Genetics and Molecular Biology"=>1}, "reader_count_by_subdiscipline"=>{"Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>4}, "Computer Science"=>{"Computer Science"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}}, "group_count"=>0}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1299278"], "description"=>"<p>Off-the-shelf kinome microarrays that the PIIKA 2 web interface allows the user to select.</p>", "links"=>[], "tags"=>["kinome", "microarrays", "piika", "interface", "allows"], "article_id"=>865453, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Earth and Environmental Sciences"], "users"=>["Brett Trost", "Jason Kindrachuk", "Pekka Määttänen", "Scott Napper", "Anthony Kusalik"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0080837.t001", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Off_the_shelf_kinome_microarrays_that_the_PIIKA_2_web_interface_allows_the_user_to_select_/865453", "title"=>"Off-the-shelf kinome microarrays that the PIIKA 2 web interface allows the user to select.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-11-29 03:14:33"}
  • {"files"=>["https://ndownloader.figshare.com/files/1299263"], "description"=>"<p>Samples were taken at four time points from six different subjects, here labeled A-F. The number of the sample from the same subject represents the time point at which the sample was taken; for example, sample C-3 was taken from subject C at time point 3. The distance metric used for clustering was (1 - Pearson correlation), while the linkage method used was average linkage.</p>", "links"=>[], "tags"=>["hierarchical", "clustering", "kinome", "microarray", "profiles"], "article_id"=>865438, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Earth and Environmental Sciences"], "users"=>["Brett Trost", "Jason Kindrachuk", "Pekka Määttänen", "Scott Napper", "Anthony Kusalik"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0080837.g001", "stats"=>{"downloads"=>4, "page_views"=>114, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Heatmap_and_hierarchical_clustering_of_kinome_microarray_profiles_from_the_example_experiment_/865438", "title"=>"Heatmap and hierarchical clustering of kinome microarray profiles from the example experiment.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-11-29 03:14:33"}
  • {"files"=>["https://ndownloader.figshare.com/files/1299274"], "description"=>"<p>Each point represents a peptide, and the and values of that point represent the normalized intensity values for that peptide for the first sample (A-1) and the second sample (A-2), respectively. The blue line represents the best fit using least squares, whereas the red line simply shows the diagonal (). The Pearson correlation between the two samples is also indicated.</p>", "links"=>[], "tags"=>["sample-sample", "scatterplot", "generated", "piika"], "article_id"=>865449, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Earth and Environmental Sciences"], "users"=>["Brett Trost", "Jason Kindrachuk", "Pekka Määttänen", "Scott Napper", "Anthony Kusalik"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0080837.g008", "stats"=>{"downloads"=>0, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Example_of_a_sample_sample_scatterplot_generated_using_PIIKA_2_/865449", "title"=>"Example of a sample-sample scatterplot generated using PIIKA 2.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-11-29 03:14:33"}
  • {"files"=>["https://ndownloader.figshare.com/files/1299272"], "description"=>"<p>Points for which FC and P-value are coloured red, while those with FC but P-value are pale red; Similarly, points with FC and P-value are green, while those with FC but P-value are pale green. All other points are coloured black. The horizontal and vertical blue lines represent the P-value and FC cutoffs, respectively. All coloured points are accompanied by labels showing to which peptide the point corresponds.</p>", "links"=>[], "tags"=>["volcano", "generated", "piika"], "article_id"=>865447, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Earth and Environmental Sciences"], "users"=>["Brett Trost", "Jason Kindrachuk", "Pekka Määttänen", "Scott Napper", "Anthony Kusalik"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0080837.g007", "stats"=>{"downloads"=>1, "page_views"=>31, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Example_of_a_volcano_plot_generated_using_PIIKA_2_/865447", "title"=>"Example of a volcano plot generated using PIIKA 2.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-11-29 03:14:33"}
  • {"files"=>["https://ndownloader.figshare.com/files/1299268"], "description"=>"<p>The same distance metric and linkage method were used as in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0080837#pone-0080837-g001\" target=\"_blank\">Figure 1</a>. The sample names are the same as in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0080837#pone-0080837-g001\" target=\"_blank\">Figure 1</a>; the peptide names are also indicated on the right side of each row.</p>", "links"=>[], "tags"=>["hierarchical", "clustering", "kinome", "microarray", "profiles", "samples", "17", "peptides", "chosen"], "article_id"=>865443, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Earth and Environmental Sciences"], "users"=>["Brett Trost", "Jason Kindrachuk", "Pekka Määttänen", "Scott Napper", "Anthony Kusalik"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0080837.g004", "stats"=>{"downloads"=>1, "page_views"=>28, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Heatmap_and_hierarchical_clustering_of_kinome_microarray_profiles_of_samples_from_the_example_experiment_using_17_peptides_chosen_according_to_a_local_search_algorithm_/865443", "title"=>"Heatmap and hierarchical clustering of kinome microarray profiles of samples from the example experiment using 17 peptides chosen according to a local search algorithm.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-11-29 03:14:33"}
  • {"files"=>["https://ndownloader.figshare.com/files/1299267"], "description"=>"<p>Ten thousand random matrices were created from the matrix used to create the sample dendrogram in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0080837#pone-0080837-g001\" target=\"_blank\">Figure 1</a> by randomly rearranging the peptide intensity values within each sample. For each score that was given to at least one random tree, the frequency of that score is indicated.</p>", "links"=>[], "tags"=>[], "article_id"=>865442, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Earth and Environmental Sciences"], "users"=>["Brett Trost", "Jason Kindrachuk", "Pekka Määttänen", "Scott Napper", "Anthony Kusalik"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0080837.g003", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Empirical_distribution_of_random_tree_scores_/865442", "title"=>"Empirical distribution of random tree scores.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-11-29 03:14:33"}
  • {"files"=>["https://ndownloader.figshare.com/files/1299280", "https://ndownloader.figshare.com/files/1299281", "https://ndownloader.figshare.com/files/1299282", "https://ndownloader.figshare.com/files/1299283", "https://ndownloader.figshare.com/files/1299284"], "description"=>"<div><p>Kinome microarrays are comprised of peptides that act as phosphorylation targets for protein kinases. This platform is growing in popularity due to its ability to measure phosphorylation-mediated cellular signaling in a high-throughput manner. While software for analyzing data from DNA microarrays has also been used for kinome arrays, differences between the two technologies and associated biologies previously led us to develop Platform for Intelligent, Integrated Kinome Analysis (PIIKA), a software tool customized for the analysis of data from kinome arrays. Here, we report the development of PIIKA 2, a significantly improved version with new features and improvements in the areas of clustering, statistical analysis, and data visualization. Among other additions to the original PIIKA, PIIKA 2 now allows the user to: evaluate statistically how well groups of samples cluster together; identify sets of peptides that have consistent phosphorylation patterns among groups of samples; perform hierarchical clustering analysis with bootstrapping; view false negative probabilities and positive and negative predictive values for t-tests between pairs of samples; easily assess experimental reproducibility; and visualize the data using volcano plots, scatterplots, and interactive three-dimensional principal component analyses. Also new in PIIKA 2 is a web-based interface, which allows users unfamiliar with command-line tools to easily provide input and download the results. Collectively, the additions and improvements described here enhance both the breadth and depth of analyses available, simplify the user interface, and make the software an even more valuable tool for the analysis of kinome microarray data. Both the web-based and stand-alone versions of PIIKA 2 can be accessed via <a href=\"http://saphire.usask.ca\" target=\"_blank\">http://saphire.usask.ca</a>.</p></div>", "links"=>[], "tags"=>["web-based", "kinome", "microarray"], "article_id"=>865455, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Earth and Environmental Sciences"], "users"=>["Brett Trost", "Jason Kindrachuk", "Pekka Määttänen", "Scott Napper", "Anthony Kusalik"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0080837.s001", "https://dx.doi.org/10.1371/journal.pone.0080837.s002", "https://dx.doi.org/10.1371/journal.pone.0080837.s003", "https://dx.doi.org/10.1371/journal.pone.0080837.s004", "https://dx.doi.org/10.1371/journal.pone.0080837.s005"], "stats"=>{"downloads"=>0, "page_views"=>18, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_PIIKA_2_An_Expanded_Web_Based_Platform_for_Analysis_of_Kinome_Microarray_Data_/865455", "title"=>"PIIKA 2: An Expanded, Web-Based Platform for Analysis of Kinome Microarray Data", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2013-11-29 03:14:33"}
  • {"files"=>["https://ndownloader.figshare.com/files/1299276"], "description"=>"<p>Screenshot of the user interface of the PIIKA 2 web server.</p>", "links"=>[], "tags"=>["interface", "piika"], "article_id"=>865451, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Earth and Environmental Sciences"], "users"=>["Brett Trost", "Jason Kindrachuk", "Pekka Määttänen", "Scott Napper", "Anthony Kusalik"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0080837.g009", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Screenshot_of_the_user_interface_of_the_PIIKA_2_web_server_/865451", "title"=>"Screenshot of the user interface of the PIIKA 2 web server.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-11-29 03:14:33"}
  • {"files"=>["https://ndownloader.figshare.com/files/1299270"], "description"=>"<p>In this experiment, samples were taken from subjects labeled A, B, C, D, E, and F. Samples corresponding to subject A are in red, subject B are in yellow, and so on. The label near the top of the figure is the result of hovering the mouse over the leftmost red circle, and shows that the first, second, and third principal components for this sample had the values 2.46, 1.48, and 1.03, respectively. This image is an example of the visualization given using the VRML viewer Instant Player ( <a href=\"http://www.instantreality.org\" target=\"_blank\">http://www.instantreality.org</a> ).</p>", "links"=>[], "tags"=>["pca", "generated", "vrml", "piika"], "article_id"=>865445, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Earth and Environmental Sciences"], "users"=>["Brett Trost", "Jason Kindrachuk", "Pekka Määttänen", "Scott Napper", "Anthony Kusalik"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0080837.g006", "stats"=>{"downloads"=>0, "page_views"=>19, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Example_of_a_PCA_plot_generated_in_VRML_format_by_PIIKA_2_/865445", "title"=>"Example of a PCA plot generated in VRML format by PIIKA 2.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-11-29 03:14:33"}
  • {"files"=>["https://ndownloader.figshare.com/files/1299269"], "description"=>"<p>The clustering of the samples is the same as in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0080837#pone-0080837-g001\" target=\"_blank\">Figure 1</a>. The red numbers represent the approximately unbiased (AU) P-values as determined using the method of Shimodaira <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0080837#pone.0080837-Shimodaira1\" target=\"_blank\">[17]</a>, <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0080837#pone.0080837-Shimodaira2\" target=\"_blank\">[18]</a>, while the green numbers represent the standard bootstrap P-value <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0080837#pone.0080837-Felenstein1\" target=\"_blank\">[16]</a>. All calculations and the drawing of the figure were performed using the R package pvclust <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0080837#pone.0080837-Suzuki1\" target=\"_blank\">[19]</a>.</p>", "links"=>[], "tags"=>["dendrogram", "bootstrap", "piika"], "article_id"=>865444, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Earth and Environmental Sciences"], "users"=>["Brett Trost", "Jason Kindrachuk", "Pekka Määttänen", "Scott Napper", "Anthony Kusalik"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0080837.g005", "stats"=>{"downloads"=>7, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Example_of_a_dendrogram_with_bootstrap_values_using_PIIKA_2_/865444", "title"=>"Example of a dendrogram with bootstrap values using PIIKA 2.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-11-29 03:14:33"}
  • {"files"=>["https://ndownloader.figshare.com/files/1299266"], "description"=>"<p>Leaf nodes are shaded in grey and are labeled according to the subject and time point as in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0080837#pone-0080837-g001\" target=\"_blank\">Figure 1</a>. Internal nodes are labeled through , and those internal nodes for which is maximized for some group (where corresponds to subject A, corresponds to subject B, and so on; see also <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0080837#pone.0080837.e013\" target=\"_blank\">Equation 1</a>) are shaded in blue.</p>", "links"=>[], "tags"=>["dendrogram"], "article_id"=>865441, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Earth and Environmental Sciences"], "users"=>["Brett Trost", "Jason Kindrachuk", "Pekka Määttänen", "Scott Napper", "Anthony Kusalik"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0080837.g002", "stats"=>{"downloads"=>0, "page_views"=>30, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Binary_tree_representation_of_the_dendrogram_shown_in_Figure_1_/865441", "title"=>"Binary tree representation of the dendrogram shown in Figure 1.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-11-29 03:14:33"}

PMC Usage Stats | Further Information

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Relative Metric

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