A class generated from the function RegulatoryEnrichment() containing the overrepresented post-transcriptional regulatory factors (RBPs, miRNAs, etc) from the lists of differentially expressed genes coming from the analysis of two different expression levels.
Slots
enriched.table:
Object of class data.frame containing all the regulatory enrichment analysis. The data frame contains one row for each regulatory factor, while columns are organized as follows:
level, level of analysis on which the enrichment is calculated. The names of the two levels are taken from the object DEGs given as an input to the function GOEnrichment.
ID, ID of the regulatory factor.
number, number of genes in the human genome associated to the regulatory factor.
list, list of genes in the list of DEGs associated to the regulatory factor.
pv.fisher, enrichment p-value calculated with the Fisher test.
pv.fisher.BH, the Benjamini-Hochberg corrected enrichment p-value calculated with the Fisher test according to the chosen enrichment method.
label.level.enriched:
Object of class character specifying the names of the two levels compared in the experiment.
Accessors
enriched.table
signature(object = "EnrichedSets"): displays the slot enriched.table.
label.level.enriched
signature(object = "EnrichedSets"): displays the slot label.level.enriched, slot of class character specifying the names of the two levels compared in the experiment.
Methods
Heatmap
signature(object = "EnrichedSets"): enables the generation of a heatmap of the top enriched regulatory factors for the first and second level of analysis.
label.level.enriched
signature(object = "EnrichedSets"): displays the slot label.level.enriched.
Radar
signature(object = "EnrichedSets"): enables the generation of a radar plot of the top enriched regulatory factors for the first and second level of analysis.
show
signature(object = "EnrichedSets"): displays all the two slots of the class.
Author(s)
Erik Dassi, Toma Tebaldi
References
Alexa A, Rahnenfuhrer J, Lengauer T. Improved scoring of functional groups from gene expression data by decorrelating go graph structure. Bioinformatics 2006, 22(13):1600-7.
Dassi E et al(2012). AURA: Atlas of UTR Regulatory Activity. Bioinformatics. 28(1):142-4.
See Also
GOsetsDEGs
Examples
showClass("EnrichedSets")
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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> library(tRanslatome)
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rbind, rownames, sapply, setdiff, sort, table, tapply, union,
unique, unsplit
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> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/tRanslatome/EnrichedSets.Rd_%03d_medium.png", width=480, height=480)
> ### Name: EnrichedSets-class
> ### Title: Class 'EnrichedSets'
> ### Aliases: EnrichedSets-class enriched.table,EnrichedSets-method
> ### label.level.enriched,EnrichedSets-method Radar,EnrichedSets-method
> ### Heatmap,EnrichedSets-method show,EnrichedSets-method
> ### Keywords: classes GO enrichment analysis
>
> ### ** Examples
>
> showClass("EnrichedSets")
Class "EnrichedSets" [package "tRanslatome"]
Slots:
Name: enriched.table label.level.enriched
Class: data.frame character
Known Subclasses: "GOsets"
>
>
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> dev.off()
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providing 
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