ArticleNucleic acids research2014
EDDY: a novel statistical gene set test method to detect differential genetic dependencies.
Article in Nucleic acids research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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19 citing papers in PubMed.
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- Evolving Schema for Employing Network Biology Approaches to Understand Pulmonary Hypertension.Advances in experimental medicine and biology · 2021Article
- Systems Analysis of the Human Pulmonary Arterial Hypertension Lung Transcriptome.American journal of respiratory cell and molecular biology · 2019Article
- End Stage Takes Center Stage in Pulmonary Arterial Hypertension.American journal of respiratory cell and molecular biology · 2019Article
- Evolving systems biology approaches to understanding non-coding RNAs in pulmonary hypertension.The Journal of physiology · 2019Review
- Network Rewiring in Cancer: Applications to Melanoma Cell Lines and the Cancer Genome Atlas Patients.Frontiers in genetics · 2018Article
- Contextualization of drug-mediator relations using evidence networks.BMC bioinformatics · 2017Article
- Review
- CTD2 Dashboard: a searchable web interface to connect validated results from the Cancer Target Discovery and Development Network.Database : the journal of biological databases and curation · 2017Article
- Bayesian model of signal rewiring reveals mechanisms of gene dysregulation in acquired drug resistance in breast cancer.PloS one · 2017Article
- DIFFERENTIAL PATHWAY DEPENDENCY DISCOVERY ASSOCIATED WITH DRUG RESPONSE ACROSS CANCER CELL LINES.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2017Article
- Review
- Comprehensive Pan-Genomic Characterization of Adrenocortical Carcinoma.Cancer cell · 2016Article
- Gene set analysis using sufficient dimension reduction.BMC bioinformatics · 2016Article
- KNOWLEDGE-ASSISTED APPROACH TO IDENTIFY PATHWAYS WITH DIFFERENTIAL DEPENDENCIES.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2016Article
- ChiNet uncovers rewired transcription subnetworks in tolerant yeast for advanced biofuels conversion.Nucleic acids research · 2015Article
- Article
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Abstract
Identifying differential features between conditions is a popular approach to understanding molecular features and their mechanisms underlying a biological process of particular interest. Although many tests for identifying differential expression of gene or gene sets have been proposed, there was limited success in developing methods for differential interactions of genes between conditions because of its computational complexity. We present a method for Evaluation of Dependency DifferentialitY (EDDY), which is a statistical test for differential dependencies of a set of genes between two conditions. Unlike previous methods focused on differential expression of individual genes or correlation changes of individual gene-gene interactions, EDDY compares two conditions by evaluating the probability distributions of dependency networks from genes. The method has been evaluated and compared with other methods through simulation studies, and application to glioblastoma multiforme data resulted in informative cancer and glioblastoma multiforme subtype-related findings. The comparison with Gene Set Enrichment Analysis, a differential expression-based method, revealed that EDDY identifies the gene sets that are complementary to those identified by Gene Set Enrichment Analysis. EDDY also showed much lower false positives than Gene Set Co-expression Analysis, a method based on correlation changes of individual gene-gene interactions, thus providing more informative results. The Java implementation of the algorithm is freely available to noncommercial users. Download from: http://biocomputing.tgen.org/software/EDDY.
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