Fastukb is an innovative tool specially developed to rationalize and improve research workflows using British biobank, effectively approaching the key limits of existing platforms such as the British Biobank Research Platform (RAP). One of its most notable features is its revolutionary functionality to extraction to bulk data, which transforms the traditionally complex coding tasks in intuitive clicks. This is made possible thanks to a user -friendly interface equipped with drop -down menus and a hierarchical variable tree structure, allowing researchers to navigate effortlessly and select the data they need. Unlike RAP, which prevents users from selecting only 30 variables at a time-a significant obstacle to analytical-fastukb efficiency allows the extraction of an unlimited number of variables in a single operation. In addition, it supports data extraction on several entities, including participants data (encompassing basic demographic information and clinical phenotypes), Olink_instance proteomics data, genomic data, neuroimagery and cardiac imagery data, metabolomic data and monitoring the physical activity_monitor, among others. Compared to existing tools such as Ukbrast and Ukbtools, Fastukb stands out by offering wider lots’ extraction capacities, automated correspondence in the field and a much lower technical barrier, which makes it accessible to a wider range of researchers.
Beyond the extraction of data, FastukB works as a complete center for intelligent processing and analysis of data, providing end-to-end support throughout the search process, from data cleaning to advanced statistical analysis. Its integrated medical quality control module is designed to manage the unique challenges of British Biobanques, automatically identify and process the missing values marked by special encodings such as -1, -3 and -7, and detect aberrant values based on medical expertise to report physiologically unreasonable values. In addition, it converts the unique coding system of UK Biobank into standard familiar classifications to researchers and validates the logical coherence between the related variables to ensure the reliability of the analytical foundation. Fastukb also simplifies the often long task of generating basic characteristic tables that meet the standards of high -level medical journals. By allowing users to select variables and grouping methods, the tool automatically chooses appropriate statistical methods based on the data type and distribution, performs relevant statistical tests to calculate P values between groups and generates the basic table in a transparent manner. In addition, it offers a wide range of advanced statistical analysis tools, in particular linear regression, logistical regression, COX proportional risk models, analysis of subgroups, interaction analysis, polygeenic risks and sensitivity analysis-all accessible thanks to simple parameters, eliminating the need for a complex coding.
Another key advantage of Fastukb is its download of personalized variable and its intelligent correspondence system, which considerably improves flexibility and the applicability of the tool. Researchers can download personalized ID lists in CSV, XLSX or TXT formats, and the system will intelligently correspond to data from these specific samples, facilitating a precise selection of samples for various epidemiological study conceptions such as cohort and casual presentation studies. For example, in case control studies, users can download paired control group IDs, and the system can even automatically identify the most appropriate paired samples within British biobank on the basis of specific variables such as age, sex and socioeconomic status. This system also supports the download of personalized variables for integration with British Biobank Brutes Data, including external data from other platforms, derived variables such as disease risk scores, and ensures clear control of data versions to distinguish original data and downloaded by the user.
Fastukb has already proven its value in practical applications. In a study exploring the relationship between sleep habits, genetic risk and incident rheumatoid arthritis, the tool has effectively extracted sleep behavior indicators of 375,133 participants. Similarly, in a study studying plasma metabolite profiles linked to the Eat-lancet diet and inflammatory intestine diseases, it facilitated the treatment of nearly 900 metabolites, allowing researchers to focus on scientific questions rather than technical details. Although it is currently adapted to the Biobank data structure and the variable coding system of the United Kingdom, the modular architecture of FastukB is designed for scalability, the future development potentially extending its framework to accommodate other large-scale biomedical data sets like Finngen or all. By lowering the barrier to the access and analysis of large sets of biomedical data, FastukB democratizes research, accelerates the research cycle, improves the quality of research and ultimately contributes to advancing medical knowledge and translating the results in clinical practice.