reg2gene R package was build to perform 2 main categories of tasks: - 1. to predict target genes for regulatory elements genome-wide by building "gene expression - enhancer activity" models by performing: - DATA INTEGRATION - extracting information stored in bigWig files (across different cell types) to - a. quantifying (enhancer) activity (regulatory potential) for genomic regions of interest (enhancer regions), and - b. quantifying gene expression for genes of interest, and/or - c. combining these informations into one object used further for modelling - DATA MODELLING (including performance assessment) - modelling gene expression - enhancer activity using different algorithms, and combine different models with meta-analysis and voting procedure. Additionally, one can benchmark results and obtain confusion matrix. - DATA VISUALIZATION - visualization of interactions as loops in the context of the genome - 2. to annotate genomic regions (ChIP-Seq peaks or similar regions in the genome) to genes they are associated with based on the modelled enhancer-gene associations. Optionally one can as well associate genes with diseases reported in the disease-gene databases.
|Author||person("Inga", "Patarcic", email = "[email protected]", role = c("aut", "cre"), person("Altuna", "Akalin", email = "[email protected]", role=c("aut", "cre"))))|
|Maintainer||Inga Patarcic <[email protected]>|
|Package repository||View on GitHub|
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