A Multivariate Biomarker for Parkinson’s Disease
Date
2015-05-15
Journal Title
Journal ISSN
Volume Title
Publisher
In the Proceedings of 12th Annual Research Day, 2014 - Pace University
Abstract
In this study, we executed a genomic analysis with the objective of selecting a set of genes (possibly small) that would help in the detection and classification of samples from patients affected by Parkinson Disease. We performed a complete data analysis and during the exploratory phase, we selected a list of differentially expressed genes. Despite their association with the diseased state, we could not use them as a biomarker tool. Therefore, our research was extended to include a multivariate analysis approach resulting in the identification and selection of a group of 20 genes that showed a clear potential in detecting and correctly classify Parkinson Disease samples even in the presence of other neurodegenerative disorders.
Description
In this study, we executed a genomic analysis with
the objective of selecting a set of genes (possibly small) that would
help in the detection and classification of samples from patients
affected by Parkinson Disease. We performed a complete data
analysis and during the exploratory phase, we selected a list of
differentially expressed genes. Despite their association with the
diseased state, we could not use them as a biomarker tool.
Therefore, our research was extended to include a multivariate
analysis approach resulting in the identification and selection of a
group of 20 genes that showed a clear potential in detecting and
correctly classify Parkinson Disease samples even in the presence
of other neurodegenerative disorders.
Keywords
Citation
M Coakley, G Crocetti, P Dressner, W Kellum, T Lamin - arXiv preprint arXiv:1505.06967, 2015