CoNet app: inference of biological association networks using Cytoscape

By Karoline Faust, Jeroen Raes. F1000Research, 2016

514 citations recorded by the source corpus.

Here we present the Cytoscape app version of our association network inference tool CoNet. Though CoNet was developed with microbial community data from sequencing experiments in mind, it is designed to be generic and can detect associations in any data set where biological entities (such as genes, metabolites or species) have been observed repeatedly. The CoNet app supports Cytoscape 2.x and 3.x and offers a variety of network inference approaches, which can also be combined. Here we briefly describe its main features and illustrate its use on microbial count data obtained by 16S rDNA sequencing of arctic soil samples. The CoNet app is available at: http://apps.cytoscape.org/apps/conet.

Subfields: Ecology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/5c8c7227dde4c0db421f28e0b5ab75e752d0c439

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Citations in the corpus

Disentangling Interactions in the Microbiome: A Network Perspective (2016, methodology): “Faust et al. [19] developed a permutation-renormalization bootstrap method (ReBoot) to evaluate the significance of Pearson's correlation coefficients (as well as other similarity, dissimilarity and correlation measures; packaged in a tool called CoNet [65]) estimated from compositional data while m”
Network analysis methods for studying microbial communities: A mini review (2021, methodology): “Another strategy that was proposed to improve the robustness of correlation coefﬁcients is bootstrapping as implemented in CoNet [24].”