{"id":122,"date":"2019-03-11T00:00:00","date_gmt":"2019-03-11T00:00:00","guid":{"rendered":"https:\/\/www.thermofisher.com\/blog\/connectedlab\/location-analytics-gain-insights-from-all-your-data\/"},"modified":"2019-08-19T16:31:32","modified_gmt":"2019-08-19T16:31:32","slug":"location-analytics-gain-insights-from-all-your-data","status":"publish","type":"post","link":"https:\/\/www.thermofisher.com\/blog\/connectedlab\/location-analytics-gain-insights-from-all-your-data\/","title":{"rendered":"Location Analytics: Gain Insights from All Your Data"},"content":{"rendered":"<h2>An Interactive Mapping Feature Associating Data and Location to Derive New Scientific Insights<\/h2>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignright wp-image-323 size-medium\" src=\"https:\/\/www.thermofisher.com\/blog\/wp-content\/uploads\/sites\/14\/2019\/07\/Location-Analytics-Gain-Insights-from-All-Your-Data-300x265.jpg\" alt=\"Using location analytics in the laboratory to better understand data\" width=\"300\" height=\"265\" \/><br \/>\nThe <a href=\"https:\/\/www.coreinformatics.com\/platform-for-science\/\">Thermo Fisher\u2122 Platform for Science\u2122 software<\/a> integration with Shiny\u00ae from RStudio\u00ae<a href=\"#_ftn1\" name=\"_ftnref1\">[1]<\/a> is enhancing reporting capabilities for organizations where associating data with its location is critical. We are extending the breadth of statistical tools available in Platform for Science software, enabling fully integrated laboratories to visualize, understand and interact with their data in new ways.<\/p>\n<h2>Why is Location Analytics Important?<\/h2>\n<p>A powerful example of location analytics is the massive amount of data collected in clinical trials. Clinical trials have grown in duration and complexity, and regulatory requirements have also increased. An avalanche of data arriving from many different trial sources and CROs present challenges to organizations. It\u2019s essential to structure and organize all the data including clinical site locations and metrics, making it accessible, insuring accuracy and advancing medical knowledge. These trials need to be able to aggregate data, but drill into it if necessary, to account to determine which data points or trends could be impacted by their subjects\u2019 environment.<\/p>\n<p>Our newest Shiny application uses the Leaflet R Package \u00a9. This R package is one of the most popular tools available for interactive maps. It\u2019s used by multiple organizations including The Washington Post, The New York Times, GitHub and Flickr. These organizations use interactive maps and location analytics to better serve their customers by offering pertinent information.<\/p>\n<h2>A Complete Clinical Analytics Workflow<\/h2>\n<p>Our new Clinical Data Explorer Shiny Application used in combination with our <a href=\"https:\/\/marketplace.coreinformatics.com\/collections\/biobanking\/products\/clinical-study-management\">Clinical Study Management<\/a>, <a href=\"https:\/\/marketplace.coreinformatics.com\/collections\/biobanking\/products\/clinical-specimen-accessioning\">Clinical Specimen Accessioning<\/a>, and <a href=\"https:\/\/marketplace.coreinformatics.com\/collections\/biobanking\">Biobanking<\/a> applications provide actionable intelligence, allowing the user to interact with the data as soon as it is collected and empower data-driven decision-making. Laboratories now have a comprehensive solution to quickly and securely define clinical studies, including associated participants, sites and groups, to approvals and build and maintain full chain-of-custody for accessioned clinical specimens.<\/p>\n<h2>Flexible Dashboarding and Reporting Capabilities<\/h2>\n<p>Visualizations include a multilayered map chart, tree map and tabular representations of the data to summarize large multiparameter clinical datasets. The application allows interactive data filtering by marking sections of the map chart or using filters in a side panel. Users can save and export results in PDF and HTML formats.<\/p>\n<p>&nbsp;<\/p>\n<h3>Complete Clinical Study Data Insight<\/h3>\n<p>&nbsp;<\/p>\n<h3>Drill Down on Study Details<\/h3>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-11591 size-full aligncenter\" src=\"http:\/\/www.coreinformatics.com\/wp-content\/uploads\/Clinical-Data-Explorer-App_Patient-Distribution-Map-and-Clinical-Details-Map.gif\" alt=\"Clinical trial details including clinical site distribution and patient distribution\" width=\"1200\" height=\"675\" \/><\/p>\n<p>&nbsp;<\/p>\n<h3>Aggregate and Analyze Data in One Platform<\/h3>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-11596 size-full aligncenter\" src=\"http:\/\/www.coreinformatics.com\/wp-content\/uploads\/Aggregate-and-Analyze-Data-in-one-platform_v2.png\" alt=\"Aggregate and analyze clinical data in one platform\" width=\"1920\" height=\"872\" \/><\/p>\n<p>&nbsp;<\/p>\n<h2>Welcome to the R Community<\/h2>\n<p>Thermo Fisher Scientific is an official RStudio reseller and we are creating a catalog of Shiny applications for Platform for Science software, designed to flexibly support the changing needs of modern laboratories, integrate data sources, and speed informatics deployments. Our applications will cover a wide range of academic and biopharma use cases including macromolecule drug discovery, in vitro data analysis, in vivo data analysis, genomics and 3D sample rendering. They will include an array of statistical techniques including supervised and unsupervised machine learning, logistic regression and multi-linear analysis.<\/p>\n<p><a href=\"#_ftnref1\" name=\"_ftn1\">[1]<\/a> RStudio and Shiny are trademarks of RStudio, Inc.<\/p>\n<hr \/>\n<p><em>Natasha Mora is a Data Scientist at Thermo Fisher Scientific.<\/em> <em>Her scientific expertise and experience allow her to better understand the problems facing our customers. Previously, Natasha was a Data Scientist focused on human and environmental health. Natasha researched<\/em> <em>Coenzyme Q10 and Heart Failure at the University of Granada<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>An Interactive Mapping Feature Associating Data and Location to Derive New Scientific Insights The Thermo Fisher\u2122 Platform for Science\u2122 software integration with Shiny\u00ae from RStudio\u00ae[1] is enhancing reporting capabilities for organizations where associating data with its location is critical. We are extending the breadth of statistical tools available in Platform for Science software, enabling fully<\/p>\n","protected":false},"author":1032,"featured_media":334,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_kad_blocks_custom_css":"","_kad_blocks_head_custom_js":"","_kad_blocks_body_custom_js":"","_kad_blocks_footer_custom_js":"","_monsterinsights_skip_tracking":false,"_genesis_hide_title":false,"_genesis_hide_breadcrumbs":false,"_genesis_hide_singular_image":false,"_genesis_hide_footer_widgets":false,"_genesis_custom_body_class":"","_genesis_custom_post_class":"","_genesis_layout":"","_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_feature_clip_id":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_post_was_ever_published":false},"categories":[89],"tags":[212,213,119,214,99,165,166,215,120],"division":[],"class_list":{"0":"post-122","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-technology","8":"tag-clinical-analytics","9":"tag-clinical-trials","10":"tag-data-analysis-and-visualization","11":"tag-location-analytics","12":"tag-platform-for-science","13":"tag-rstudio","14":"tag-shiny","15":"tag-statistical-tools","16":"tag-visualization","17":"entry"},"_selected_authors":"","_selected_reviewers":"","acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v27.8 (Yoast SEO v27.8) - 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