Publicación:
Guidelines for correlation coefficient threshold settings in metabolite correlation networks exemplified on a potato association panel

dc.contributor.author Toubiana D. es_PE
dc.contributor.author Maruenda H. es_PE
dc.date.accessioned 2024-05-30T23:13:38Z
dc.date.available 2024-05-30T23:13:38Z
dc.date.issued 2021
dc.description.abstract Background: Correlation network analysis has become an integral tool to study metabolite datasets. Networks are constructed by omitting correlations between metabolites based on two thresholds—namely the r and the associated p-values. While p-value threshold settings follow the rules of multiple hypotheses testing correction, guidelines for r-value threshold settings have not been defined. Results: Here, we introduce a method that allows determining the r-value threshold based on an iterative approach, where different networks are constructed and their network topology is monitored. Once the network topology changes significantly, the threshold is set to the corresponding correlation coefficient value. The approach was exemplified on: (i) a metabolite and morphological trait dataset from a potato association panel, which was grown under normal irrigation and water recovery conditions; and validated (ii) on a metabolite dataset of hearts of fed and fasted mice. For the potato normal irrigation correlation network a threshold of Pearson’s
dc.description.abstract r
dc.description.abstract ? 0.23 was suggested, while for the water recovery correlation network a threshold of Pearson’s
dc.description.abstract r
dc.description.abstract ? 0.41 was estimated. For both mice networks the threshold was calculated with Pearson’s
dc.description.abstract r
dc.description.abstract ? 0.84. Conclusions: Our analysis corrected the previously stated Pearson’s correlation coefficient threshold from 0.4 to 0.41 in the water recovery network and from 0.4 to 0.23 for the normal irrigation network. Furthermore, the proposed method suggested a correlation threshold of 0.84 for both mice networks rather than a threshold of 0.7 as applied earlier. We demonstrate that the proposed approach is a valuable tool for constructing biological meaningful networks. © 2021, The Author(s).
dc.description.sponsorship Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - Concytec
dc.identifier.doi https://doi.org/10.1186/s12859-021-03994-z
dc.identifier.scopus 2-s2.0-85102391682
dc.identifier.uri https://hdl.handle.net/20.500.12390/2312
dc.language.iso eng
dc.publisher BioMed Central Ltd
dc.relation.ispartof BMC Bioinformatics
dc.rights info:eu-repo/semantics/openAccess
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Threshold settings
dc.subject Correlation coefficient es_PE
dc.subject Metabolism es_PE
dc.subject Metabolite correlation network es_PE
dc.subject Mouse heart metabolism es_PE
dc.subject Pearson correlation es_PE
dc.subject Potato association panel es_PE
dc.subject.ocde http://purl.org/pe-repo/ocde/ford#3.02.18
dc.title Guidelines for correlation coefficient threshold settings in metabolite correlation networks exemplified on a potato association panel
dc.type info:eu-repo/semantics/article
dspace.entity.type Publication
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