ArticleNucleic acids research2014
Hunting complex differential gene interaction patterns across molecular contexts.
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 5 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Meta-Analysis of Differential Connectivity in Gene Co-Expression Networks in Multiple Sclerosis.International journal of molecular sciences · 2016Pooled it
- A fraction of barrier-to-autointegration factor (BAF) associates with centromeres and controls mitosis progression.Communications biology · 2020Article
- Nonmonotonic Pathway Gene Expression Analysis Reveals Oncogenic Role of p27/Kip1 at Intermediate Dose.Cancer informatics · 2017Article
- ChiNet uncovers rewired transcription subnetworks in tolerant yeast for advanced biofuels conversion.Nucleic acids research · 2015Article
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Authors and funding
5 authors.
Funding
Abstract
Heterogeneity in genetic networks across different signaling molecular contexts can suggest molecular regulatory mechanisms. Here we describe a comparative chi-square analysis (CPχ(2)) method, considerably more flexible and effective than other alternatives, to screen large gene expression data sets for conserved and differential interactions. CPχ(2) decomposes interactions across conditions to assess homogeneity and heterogeneity. Theoretically, we prove an asymptotic chi-square null distribution for the interaction heterogeneity statistic. Empirically, on synthetic yeast cell cycle data, CPχ(2) achieved much higher statistical power in detecting differential networks than alternative approaches. We applied CPχ(2) to Drosophila melanogaster wing gene expression arrays collected under normal conditions, and conditions with overexpressed E2F and Cabut, two transcription factor complexes that promote ectopic cell cycling. The resulting differential networks suggest a mechanism by which E2F and Cabut regulate distinct gene interactions, while still sharing a small core network. Thus, CPχ(2) is sensitive in detecting network rewiring, useful in comparing related biological systems.
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Registered trials
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