ArticleImmunome research2010
Coregulation mapping based on individual phenotypic variation in response to virus infection.
Article in Immunome research, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed, 5 citations in OpenAlex.
- Induction of IFNα or IL-12 depends on differentiation of THP-1 cells in dengue infections without and with antibody enhancement.BMC infectious diseases · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGene coregulation across a population is an important aspect of the considerable variability of the human immune response to virus infection. Methodology to investigate it must rely on a number of ingredients ranging from gene clustering to transcription factor enrichment analysis.
resultsWe have developed a methodology to investigate the gene to gene correlations for the expression of 34 genes linked to the immune response of Newcastle Disease Virus (NDV) infected conventional dendritic cells (DCs) from 145 human donors. The levels of gene expression showed a large variation across individuals. We generated a map of gene co-expression using pairwise correlation and multidimensional scaling (MDS). The analysis of these data showed that among the 13 genes left after filtering for statistically significant variations, two clusters are formed. We investigated to what extent the observed correlation patterns can be explained by the sharing of transcription factors (TFs) controlling these genes. Our analysis showed that there was a significant positive correlation between MDS distances and TF sharing across all pairs of genes. We applied enrichment analysis to the TFs having binding sites in the promoter regions of those genes. This analysis, after Gene Ontology filtering, indicated the existence of two clusters of genes (CCL5, IFNA1, IFNA2, IFNB1) and (IKBKE, IL6, IRF7, MX1) that were transcriptionally co-regulated. In order to facilitate the use of our methodology by other researchers, we have also developed an interactive coregulation explorer web-based tool called CorEx. It permits the study of MDS and hierarchical clustering of data combined with TF enrichment analysis. We also offer web services that provide programmatic access to MDS, hierarchical clustering and TF enrichment analysis.
conclusionsMDS mapping based on correlation in conjunction with TF enrichment analysis represents a useful computational method to generate predictions underlying gene coregulation across a population.
Identifiers
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Registered trials
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.