{"id":12,"date":"2025-02-06T19:32:58","date_gmt":"2025-02-06T19:32:58","guid":{"rendered":"https:\/\/35.227.72.49\/?page_id=12"},"modified":"2025-02-19T19:41:26","modified_gmt":"2025-02-19T19:41:26","slug":"features","status":"publish","type":"page","link":"https:\/\/www.podvis.org\/?page_id=12","title":{"rendered":"Features"},"content":{"rendered":"\n<p class=\"has-medium-font-size\"><strong>Data Sharing&nbsp;<\/strong><\/p>\n\n\n\n<p class=\"has-medium-font-size\">Your clinical dataset can be uploaded into POD-Vis to be shared among a small team of collaborators or more widely across your research community.&nbsp;<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"936\" height=\"574\" src=\"https:\/\/www.podvis.org\/wp-content\/uploads\/2025\/02\/image-8.png\" alt=\"\" class=\"wp-image-97\" srcset=\"https:\/\/www.podvis.org\/wp-content\/uploads\/2025\/02\/image-8.png 936w, https:\/\/www.podvis.org\/wp-content\/uploads\/2025\/02\/image-8-300x184.png 300w, https:\/\/www.podvis.org\/wp-content\/uploads\/2025\/02\/image-8-768x471.png 768w\" sizes=\"auto, (max-width: 936px) 100vw, 936px\" \/><\/figure>\n\n\n\n<p class=\"has-medium-font-size\"><strong>Meta Analyses&nbsp;<\/strong><\/p>\n\n\n\n<p class=\"has-medium-font-size\">POD-Vis can be used to combine datasets from one or more studies to create meta-analyses, once the data are harmonized.&nbsp;<\/p>\n\n\n\n<p class=\"has-medium-font-size\"><strong>Data Sub-Sets&nbsp;<\/strong><br><br>A major strength of POD-Vis is the ease of creating data sub-sets: <\/p>\n\n\n\n<ul class=\"wp-block-list has-medium-font-size\">\n<li>smaller more focused datasets and <\/li>\n\n\n\n<li>diverse study groups based on demographic and clinical variables.&nbsp;&nbsp;&nbsp;<br><\/li>\n<\/ul>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"936\" height=\"822\" src=\"https:\/\/www.podvis.org\/wp-content\/uploads\/2025\/02\/image-5.png\" alt=\"Study group creation\" class=\"wp-image-94\" srcset=\"https:\/\/www.podvis.org\/wp-content\/uploads\/2025\/02\/image-5.png 936w, https:\/\/www.podvis.org\/wp-content\/uploads\/2025\/02\/image-5-300x263.png 300w, https:\/\/www.podvis.org\/wp-content\/uploads\/2025\/02\/image-5-768x674.png 768w\" sizes=\"auto, (max-width: 936px) 100vw, 936px\" \/><\/figure>\n\n\n\n<p class=\"has-medium-font-size\"><strong>Analysis Types&nbsp;<\/strong><\/p>\n\n\n\n<p class=\"has-medium-font-size\">You can create <strong>outcomes-based analyses <\/strong>where you ask:&nbsp;&nbsp;<\/p>\n\n\n\n<p class=\"has-medium-font-size\">        <em>What baseline features explain differences in a selected outcome?<\/em>&nbsp;<\/p>\n\n\n\n<p class=\"has-medium-font-size\">Or you can create<strong> predictor-based analyses <\/strong>where you ask:&nbsp;&nbsp;<\/p>\n\n\n\n<p class=\"has-medium-font-size\">        <em>How do outcomes differ between different clinical subgroups?<\/em>&nbsp;<\/p>\n\n\n\n<p class=\"has-medium-font-size\"><strong>Study Group Creation&nbsp;<\/strong><\/p>\n\n\n\n<p class=\"has-medium-font-size\">You can create one or more study groups (cohorts) from your study dataset and save these for subsequent analyses. POD-Vis provides a graphical interface for users to easily filter data using one or more variables to create and save study groups. As you filter the data, all charts are dynamically updated using brushing-and-linking technology.\u00a0<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"936\" height=\"694\" src=\"https:\/\/www.podvis.org\/wp-content\/uploads\/2025\/02\/image-6.png\" alt=\"\" class=\"wp-image-95\" srcset=\"https:\/\/www.podvis.org\/wp-content\/uploads\/2025\/02\/image-6.png 936w, https:\/\/www.podvis.org\/wp-content\/uploads\/2025\/02\/image-6-300x222.png 300w, https:\/\/www.podvis.org\/wp-content\/uploads\/2025\/02\/image-6-768x569.png 768w\" sizes=\"auto, (max-width: 936px) 100vw, 936px\" \/><\/figure>\n\n\n\n<p class=\"has-medium-font-size\"><strong>Data Analysis&nbsp;<\/strong><\/p>\n\n\n\n<p class=\"has-text-align-left has-medium-font-size\">POD-Vis allows users to explore and understand the differences in two or more of the study groups. POD-Vis provides descriptive statistics including mean, median, standard deviation, performs statistical tests (ANOVA, Mann-Whitney U, Chi-square, univariate regression), and shows graphs (line graphs, histograms, spaghetti plots, bar lots, box plots, Forest plots) to understand the differences between study groups for hypotheses generation.\u00a0<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"936\" height=\"700\" src=\"https:\/\/www.podvis.org\/wp-content\/uploads\/2025\/02\/image-7.png\" alt=\"\" class=\"wp-image-96\" srcset=\"https:\/\/www.podvis.org\/wp-content\/uploads\/2025\/02\/image-7.png 936w, https:\/\/www.podvis.org\/wp-content\/uploads\/2025\/02\/image-7-300x224.png 300w, https:\/\/www.podvis.org\/wp-content\/uploads\/2025\/02\/image-7-768x574.png 768w\" sizes=\"auto, (max-width: 936px) 100vw, 936px\" \/><\/figure>\n\n\n\n<p class=\"has-medium-font-size\"><strong>Ease of Use&nbsp;<\/strong><\/p>\n\n\n\n<p class=\"has-medium-font-size\">POD-Vis was designed for ease-of-use by non-data scientists and data scientists alike.&nbsp; The platform has an easy-to-follow step-by-step tracker to guide you through your query. No training needed! Other built-in help features include:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li class=\"has-medium-font-size\">Hover text<\/li>\n\n\n\n<li class=\"has-medium-font-size\">Help mode with more detailed guidance<\/li>\n\n\n\n<li class=\"has-medium-font-size\">Computerized wizards<\/li>\n\n\n\n<li class=\"has-medium-font-size\">Automated analyses<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Data Sharing&nbsp; Your clinical dataset can be uploaded into POD-Vis to be shared among a small team of collaborators or more widely across your research community.&nbsp; Meta Analyses&nbsp; POD-Vis can be used to combine datasets from one or more studies to create meta-analyses, once the data are harmonized.&nbsp; Data Sub-Sets&nbsp; A major strength of POD-Vis [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-12","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.podvis.org\/index.php?rest_route=\/wp\/v2\/pages\/12","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.podvis.org\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.podvis.org\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.podvis.org\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.podvis.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=12"}],"version-history":[{"count":5,"href":"https:\/\/www.podvis.org\/index.php?rest_route=\/wp\/v2\/pages\/12\/revisions"}],"predecessor-version":[{"id":101,"href":"https:\/\/www.podvis.org\/index.php?rest_route=\/wp\/v2\/pages\/12\/revisions\/101"}],"wp:attachment":[{"href":"https:\/\/www.podvis.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=12"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}