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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2017
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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. |
format | Online Article Text |
id | pubmed-6217848 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
record_format | MEDLINE/PubMed |
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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