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On the Use of Multivariate Methods for Analysis of Data from Biological Networks

Data analysis used for biomedical research, particularly analysis involving metabolic or signaling pathways, is often based upon univariate statistical analysis. One common approach is to compute means and standard deviations individually for each variable or to determine where each variable falls b...

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Detalles Bibliográficos
Autores principales: Vargason, Troy, Howsmon, Daniel P., McGuinness, Deborah L., Hahn, Juergen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6217848/
https://www.ncbi.nlm.nih.gov/pubmed/30406024
http://dx.doi.org/10.3390/pr5030036
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author Vargason, Troy
Howsmon, Daniel P.
McGuinness, Deborah L.
Hahn, Juergen
author_facet Vargason, Troy
Howsmon, Daniel P.
McGuinness, Deborah L.
Hahn, Juergen
author_sort Vargason, Troy
collection PubMed
description Data analysis used for biomedical research, particularly analysis involving metabolic or signaling pathways, is often based upon univariate statistical analysis. One common approach is to compute means and standard deviations individually for each variable or to determine where each variable falls between upper and lower bounds. Additionally, p-values are often computed to determine if there are differences between data taken from two groups. However, these approaches ignore that the collected data are often correlated in some form, which may be due to these measurements describing quantities that are connected by biological networks. Multivariate analysis approaches are more appropriate in these scenarios, as they can detect differences in datasets that the traditional univariate approaches may miss. This work presents three case studies that involve data from clinical studies of autism spectrum disorder that illustrate the need for and demonstrate the potential impact of multivariate analysis.
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spelling pubmed-62178482018-11-05 On the Use of Multivariate Methods for Analysis of Data from Biological Networks Vargason, Troy Howsmon, Daniel P. McGuinness, Deborah L. Hahn, Juergen Processes (Basel) Article Data analysis used for biomedical research, particularly analysis involving metabolic or signaling pathways, is often based upon univariate statistical analysis. One common approach is to compute means and standard deviations individually for each variable or to determine where each variable falls between upper and lower bounds. Additionally, p-values are often computed to determine if there are differences between data taken from two groups. However, these approaches ignore that the collected data are often correlated in some form, which may be due to these measurements describing quantities that are connected by biological networks. Multivariate analysis approaches are more appropriate in these scenarios, as they can detect differences in datasets that the traditional univariate approaches may miss. This work presents three case studies that involve data from clinical studies of autism spectrum disorder that illustrate the need for and demonstrate the potential impact of multivariate analysis. 2017-07-03 2017 /pmc/articles/PMC6217848/ /pubmed/30406024 http://dx.doi.org/10.3390/pr5030036 Text en http://creativecommons.org/licenses/by/4.0/ This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Vargason, Troy
Howsmon, Daniel P.
McGuinness, Deborah L.
Hahn, Juergen
On the Use of Multivariate Methods for Analysis of Data from Biological Networks
title On the Use of Multivariate Methods for Analysis of Data from Biological Networks
title_full On the Use of Multivariate Methods for Analysis of Data from Biological Networks
title_fullStr On the Use of Multivariate Methods for Analysis of Data from Biological Networks
title_full_unstemmed On the Use of Multivariate Methods for Analysis of Data from Biological Networks
title_short On the Use of Multivariate Methods for Analysis of Data from Biological Networks
title_sort on the use of multivariate methods for analysis of data from biological networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6217848/
https://www.ncbi.nlm.nih.gov/pubmed/30406024
http://dx.doi.org/10.3390/pr5030036
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