Methodological considerations for large-scale breath analysis studies : lessons from the U-BIOPRED severe asthma project
| Autor: | Ahmed, Waqar M, Brinkman, Paul, Weda, Hans, Knobel, Hugo H, Xu, Yun, Nijsen, Tamara M, Goodacre, Royston, Rattray, Nicholas, Vink, Teunis J, Santonico, Marco, Pennazza, Giorgio, Montuschi, Paolo, Sterk, Peter J, Fowler, Stephen J, Grp, U-BIOPRED Study |
|---|---|
| Přispěvatelé: | ARD - Amsterdam Reproduction and Development, AII - Inflammatory diseases, Graduate School, Pulmonology |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
severe asthma
Pulmonary and Respiratory Medicine Multivariate analysis Settore BIO/14 - FARMACOLOGIA Computer science Severe asthma Best practice Sample (statistics) 01 natural sciences RS Cohort Studies 03 medical and health sciences 0302 clinical medicine Humans breath analysis Volatile Organic Compounds business.industry 010401 analytical chemistry Sampling (statistics) Reference Standards Asthma 0104 chemical sciences Breath Tests Databases as Topic 030228 respiratory system Breath gas analysis Risk analysis (engineering) Scale (social sciences) Multivariate Analysis business Quality assurance Biomarkers |
| Zdroj: | JOURNAL OF BREATH RESEARCH Journal of breath research, 13(1). IOP Publishing Ltd. U-BIOPRED Study Group 2018, ' Methodological considerations for large-scale breath analysis studies : lessons from the U-BIOPRED severe asthma project ', Journal of Breath Research, vol. 13, no. 1 . https://doi.org/10.1088/1752-7163/aae557 |
| ISSN: | 1752-7163 |
| DOI: | 10.1088/1752-7163/aae557 |
| Popis: | Methods for breath sampling and analysis require robust quality assessment to minimise the risk of false discoveries. Planning large-scale multi-site breath metabolite profiling studies also requires careful consideration of systematic and random variation as a result of sampling and analysis techniques. In this study we use breath sample data from the recent U-BIOPRED cohort to evaluate and discuss some important methodological considerations such as batch variation and correction, variation between sites, storage and transportation, as well as inter-instrument analytical differences. Based on this we provide a summary of recommended best practices for new large scale multi-site studies. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|