ArticleScientific reports2018
Ranking genome-wide correlation measurements improves microarray and RNA-seq based global and targeted co-expression networks.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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29 citing papers in PubMed.
- Constructing gene co-functional and co-regulatory networks from public transcriptomes using condition-specific ensemble co-expression.Nature communications · 2026Article
- Inferring Gene Networks from High-Throughput Transcriptomes.Methods in molecular biology (Clifton, N.J.) · 2026Article
- The Rauvolfia tetraphylla genome suggests multiple distinct biosynthetic routes for yohimbane monoterpene indole alkaloids.Communications biology · 2023Article
- Model-based evaluation of spatiotemporal data reduction methods with unknown ground truth through optimal visualization and interpretability metrics.Briefings in bioinformatics · 2023Article
- From Classical to Modern Computational Approaches to Identify Key Genetic Regulatory Components in Plant Biology.International journal of molecular sciences · 2023Review
- MarpolBase Expression: A Web-Based, Comprehensive Platform for Visualization and Analysis of Transcriptomes in the Liverwort Marchantia polymorpha.Plant & cell physiology · 2022Article
- NetREx: Network-based Rice Expression Analysis Server for abiotic stress conditions.Database : the journal of biological databases and curation · 2022Article
- The Whole-transcriptome Landscape of Diabetes-related Sarcopenia Reveals the Specific Function of Novel lncRNA Gm20743.Communications biology · 2022Article
- Kinase-dead mutation: A novel strategy for improving soybean resistance to soybean cyst nematode Heterodera glycines.Molecular plant pathology · 2022Article
- Comparison of confound adjustment methods in the construction of gene co-expression networks.Genome biology · 2022Article
- Global transcriptome and coexpression network analyses reveal cultivar-specific molecular signatures associated with different rooting depth responses to drought stress in potato.Frontiers in plant science · 2022Article
- Unleashing the power within short-read RNA-seq for plant research: Beyond differential expression analysis and toward regulomics.Frontiers in plant science · 2022Review
- TopoFun: a machine learning method to improve the functional similarity of gene co-expression modules.NAR genomics and bioinformatics · 2021Article
- Beyond the Biosynthetic Gene Cluster Paradigm: Genome-Wide Coexpression Networks Connect Clustered and Unclustered Transcription Factors to Secondary Metabolic Pathways.Microbiology spectrum · 2021Article
- Performance of a scalable RNA extraction-free transcriptome profiling method for adherent cultured human cells.Scientific reports · 2021Article
- Topological analysis of interaction patterns in cancer-specific gene regulatory network: persistent homology approach.Scientific reports · 2021Article
- Organoid technology for personalized pancreatic cancer therapy.Cellular oncology (Dordrecht, Netherlands) · 2021Review
- ADAP is a possible negative regulator of glucosinolate biosynthesis in Arabidopsis thaliana based on clustering and gene expression analyses.Journal of plant research · 2021Article
- Modern Approaches for Transcriptome Analyses in Plants.Advances in experimental medicine and biology · 2021Article
- Identifying Genes Involved in alkaloid Biosynthesis inBiomolecules · 2020Article
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12 authors.
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Abstract
Co-expression networks are essential tools to infer biological associations between gene products and predict gene annotation. Global networks can be analyzed at the transcriptome-wide scale or after querying them with a set of guide genes to capture the transcriptional landscape of a given pathway in a process named Pathway Level Coexpression (PLC). A critical step in network construction remains the definition of gene co-expression. In the present work, we compared how Pearson Correlation Coefficient (PCC), Spearman Correlation Coefficient (SCC), their respective ranked values (Highest Reciprocal Rank (HRR)), Mutual Information (MI) and Partial Correlations (PC) performed on global networks and PLCs. This evaluation was conducted on the model plant Arabidopsis thaliana using microarray and differently pre-processed RNA-seq datasets. We particularly evaluated how dataset × distance measurement combinations performed in 5 PLCs corresponding to 4 well described plant metabolic pathways (phenylpropanoid, carbohydrate, fatty acid and terpene metabolisms) and the cytokinin signaling pathway. Our present work highlights how PCC ranked with HRR is better suited for global network construction and PLC with microarray and RNA-seq data than other distance methods, especially to cluster genes in partitions similar to biological subpathways.
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