PT  - JOURNAL ARTICLE
AU  - Zounemat Kermani, nazanin
AU  - Busby, John
AU  - Sun, Kai
AU  - Pandis, Ioannis
AU  - Gainsborough, Gabrielle
AU  - Guo, Yike
AU  - Adcock, Ian
AU  - Hardman, Tim
AU  - Heaney, Liam
TI  - A data management and analysis platform for RASP-UK multiomics clinical datasets
AID  - 10.1183/13993003.congress-2021.OA4058
DP  - 2021 Sep 05
TA  - European Respiratory Journal
PG  - OA4058
VI  - 58
IP  - suppl 65
4099  - http://erj.ersjournals.com/content/58/suppl_65/OA4058.short
4100  - http://erj.ersjournals.com/content/58/suppl_65/OA4058.full
SO  - Eur Respir J2021 Sep 05; 58
AB  - Background: United Kingdom Refractory Asthma Stratification Programme (RASP-UK) is a randomised trial of corticosteroid optimisation in severe asthma based on composite biomarkers [1]. TranSMART is an open-source data warehouse and analysis platform developed to store large amounts of clinical and omics data[2]. Using a data management platform ensures: accessibility, sustainability and transparency of data which is essential for future respiratory projects within the EU.Aim: Our aim was to deploy a tranSMART platform and to apply the extract-transform-load (ETL) process for RASP-UK datasets and with a 100% accuracy.Methods: TranSMART were deployed on the Data Science Institute (DSI) servers (https://rasp.dsi.ic.ac.uk/transmart/). After the ETL process data was uploaded to the tranSMART platform (Fig 1-A, C). The accuracy of the ETL process was confirmed by a full recompile of the study dataset from TranSMART and a field-by-field comparison with the index data (Fig 1-B).Fig1-A is a screenshot of the platform. B shows the ETL and the testing process. C shows a summary of the data.Results: A tranSMART platform were deployed and RASP-UK datasets were uploaded to the platform with a 100% accuracy.Conclusions: TranSMART platform contributes to the accessibility and sustainability of large data-centred projects.FootnotesCite this article as: European Respiratory Journal 2021; 58: Suppl. 65, OA4058.This abstract was presented at the 2021 ERS International Congress, in session “Prediction of exacerbations in patients with COPD”.This is an ERS International Congress abstract. No full-text version is available. Further material to accompany this abstract may be available at www.ers-education.org (ERS member access only).