ArticleBMC bioinformatics2018
wTO: an R package for computing weighted topological overlap and a consensus network with integrated visualization tool.
Article in BMC bioinformatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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Who cites it
33 citing papers in PubMed.
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- PDL1 targeting by miR-138-5p amplifies anti-tumor immunity and Jurkat cells survival in non-small cell lung cancer.Scientific reports · 2024Article
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- Noncoding RNAs improve the predictive power of network medicine.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Identification of genes associated with abiotic stress tolerance in sweetpotato using weighted gene co-expression network analysis.Plant direct · 2023Article
- CD8 + T-cell marker genes reveal different immune subtypes of oral lichen planus by integrating single-cell RNA-seq and bulk RNA-sequencing.BMC oral health · 2023Article
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- Measuring subjective quality of life in autistic adults with the PROMIS global-10: Psychometric study and development of an autism-specific scoring method.Autism : the international journal of research and practice · 2023Article
- Oral administration ofFrontiers in veterinary science · 2023Article
- Shared and contrasting associations in the dynamic nano- and picoplankton communities of two close but contrasting sites from the Bay of Biscay.Environmental microbiology · 2022Article
- Mapping hormone-regulated cell-cell interaction networks in the human breast at single-cell resolution.Cell systems · 2022Article
- Robust normalization and transformation techniques for constructing gene coexpression networks from RNA-seq data.Genome biology · 2022Article
- Clinical M2 Macrophage-Related Genes Can Serve as a Reliable Predictor of Lung Adenocarcinoma.Frontiers in oncology · 2022Article
- Gene Co-expression Network Analysis.Methods in molecular biology (Clifton, N.J.) · 2022Article
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Authors and funding
5 authors.
Funding
Abstract
backgroundNetwork analyses, such as of gene co-expression networks, metabolic networks and ecological networks have become a central approach for the systems-level study of biological data. Several software packages exist for generating and analyzing such networks, either from correlation scores or the absolute value of a transformed score called weighted topological overlap (wTO). However, since gene regulatory processes can up- or down-regulate genes, it is of great interest to explicitly consider both positive and negative correlations when constructing a gene co-expression network.
resultsHere, we present an R package for calculating the weighted topological overlap (wTO), that, in contrast to existing packages, explicitly addresses the sign of the wTO values, and is thus especially valuable for the analysis of gene regulatory networks. The package includes the calculation of p-values (raw and adjusted) for each pairwise gene score. Our package also allows the calculation of networks from time series (without replicates). Since networks from independent datasets (biological repeats or related studies) are not the same due to technical and biological noise in the data, we additionally, incorporated a novel method for calculating a consensus network (CN) from two or more networks into our R package. To graphically inspect the resulting networks, the R package contains a visualization tool, which allows for the direct network manipulation and access of node and link information. When testing the package on a standard laptop computer, we can conduct all calculations for systems of more than 20,000 genes in under two hours. We compare our new wTO package to state of art packages and demonstrate the application of the wTO and CN functions using 3 independently derived datasets from healthy human pre-frontal cortex samples. To showcase an example for the time series application we utilized a metagenomics data set.
conclusionIn this work, we developed a software package that allows the computation of wTO networks, CNs and a visualization tool in the R statistical environment. It is publicly available on CRAN repositories under the GPL -2 Open Source License ( https://cran.r-project.org/web/packages/wTO/ ).
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.