appTEKRABber: Visualize TEKRABber results with shiny app

View source: R/appTEKRABber.R

appTEKRABberR Documentation

Visualize TEKRABber results with shiny app


To help user explore their results using TEKRABber, this function visualizes the results using a self-written shiny app with two tabs, including the expression and correlation of genes and TEs. To run it, you need to create four variables and assign them with your DE result, correlation results and metadata to appDE, appRef, appCompare and appMeta. Please see the example below for more details.




An app to display differentially expressed genes/TEs and the correlation results


fetchData <- fetchDataHmChimp

inputBundle <- DECorrInputs(fetchData)

# create metadata for DE analysis
meta <- data.frame(species=c(rep("human", ncol(fetchData$geneRef) - 1), 
    rep("chimpanzee", ncol(fetchData$geneCompare) - 1))
rownames(meta) <- colnames(inputBundle$geneInputDESeq2)
meta$species <- factor(meta$species, levels = c("human", "chimpanzee"))

# DE analysis
hmchimpDE <- DEgeneTE(
    geneTable = inputBundle$geneInputDESeq2,
    teTable = inputBundle$teInputDESeq2,
    metadata = meta,
    expDesign = TRUE

hmGeneCorrInput <- assay_tekcorrset(speciesCorr, "gene", "human")
hmTECorrInput <- assay_tekcorrset(speciesCorr, "te", "human")
chimpGeneCorrInput <- assay_tekcorrset(speciesCorr, "gene", "chimpanzee")
chimpTECorrInput <- assay_tekcorrset(speciesCorr, "te", "chimpanzee")

# Correlation analysis
hmCorrResult <- corrOrthologTE(
    geneInput = hmGeneCorrInput,
    teInput = hmTECorrInput,
    corrMethod = "pearson",
    padjMethod = "fdr"
chimpCorrResult <- corrOrthologTE(
    geneInput = chimpGeneCorrInput,
    teInput = chimpTECorrInput,
    corrMethod = "pearson",
    padjMethod = "fdr"

# assign results and metadata to appDE, appRef, appCompare, and appMeta
appDE <- hmchimpDE
appRef <- hmCorrResult
appCompare <- chimpCorrResult
appMeta <- meta

if (interactive()){


ferygood/TEKRABber documentation built on March 11, 2023, 5:03 a.m.