Reviewing and assessing existing meta-analysis models and tools
| العنوان: | Reviewing and assessing existing meta-analysis models and tools |
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| المؤلفون: | Emile R. Chimusa, Funmilayo Makinde, Milaine S S Tchamga, Gaston K. Mazandu, Segun Fatumo, James Jafali, Nicola Mulder |
| المصدر: | Brief Bioinform |
| بيانات النشر: | Oxford University Press (OUP), 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | Data Analysis, Boosting (machine learning), Computer science, Decision Trees, Review, computer.software_genre, Data science, Workflow, Biological condition, Differentially expressed genes, Meta-Analysis as Topic, Individual study, Sample size determination, Meta-analysis, Predictive power, Humans, Molecular Biology, computer, Algorithms, Software, Information Systems, Data integration |
| الوصف: | Over the past few years, meta-analysis has become popular among biomedical researchers for detecting biomarkers across multiple cohort studies with increased predictive power. Combining datasets from different sources increases sample size, thus overcoming the issue related to limited sample size from each individual study and boosting the predictive power. This leads to an increased likelihood of more accurately predicting differentially expressed genes/proteins or significant biomarkers underlying the biological condition of interest. Currently, several meta-analysis methods and tools exist, each having its own strengths and limitations. In this paper, we survey existing meta-analysis methods, and assess the performance of different methods based on results from different datasets as well as assessment from prior knowledge of each method. This provides a reference summary of meta-analysis models and tools, which helps to guide end-users on the choice of appropriate models or tools for given types of datasets and enables developers to consider current advances when planning the development of new meta-analysis models and more practical integrative tools. |
| تدمد: | 1477-4054 1467-5463 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9b88abc3db2730a1af87911cef155613 https://doi.org/10.1093/bib/bbab324 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....9b88abc3db2730a1af87911cef155613 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 14774054 14675463 |
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