## ---- eval=FALSE--------------------------------------------------------------
# library(devtools)
# install_github('pinin4fjords/shinyngs')
## ----eval = FALSE-------------------------------------------------------------
# library(shinyngs)
#
# data(airway, package = 'airway')
# ese <- as(airway, 'ExploratorySummarizedExperiment')
# eselist <- ExploratorySummarizedExperimentList(ese)
## ----eval = FALSE-------------------------------------------------------------
# app <- prepareApp('heatmap', eselist)
# shiny::shinyApp(ui = app$ui, server = app$server)
## ----eval = FALSE-------------------------------------------------------------
# app <- prepareApp('rnaseq', eselist)
# shiny::shinyApp(ui = app$ui, server = app$server)
## ----eval = FALSE-------------------------------------------------------------
# data(airway, package = 'airway')
# expinfo <- metadata(airway)[[1]]
#
# eselist <- ExploratorySummarizedExperimentList(
# ese,
# title = expinfo@title,
# author = expinfo@name,
# description = abstract(expinfo)
# )
# app <- prepareApp('rnaseq', eselist)
# shiny::shinyApp(ui = app$ui, server = app$server)
## ----eval = FALSE-------------------------------------------------------------
# # Use Biomart to retrieve some annotation, and add it to the object
#
# library(biomaRt)
# attributes <- c(
# 'ensembl_gene_id', # The sort of ID your results are keyed by
# 'entrezgene', # Will be used mostly for gene set based stuff
# 'external_gene_name' # Used to annotate gene names on the plot
# )
#
# mart <- useMart(biomart = 'ENSEMBL_MART_ENSEMBL', dataset = 'hsapiens_gene_ensembl', host='www.ensembl.org')
# annotation <- getBM(attributes = attributes, mart = mart)
# annotation <- annotation[order(annotation$entrezgene),]
#
# mcols(ese) <- annotation[match(rownames(ese), annotation$ensembl_gene_id),]
#
# # Tell shinyngs what the ids are, and what field to use as a label
#
# ese@idfield <- 'ensembl_gene_id'
# ese@labelfield <- 'external_gene_name'
#
# # Re-build the app
#
# eselist <- ExploratorySummarizedExperimentList(
# ese,
# title = expinfo@title,
# author = expinfo@name,
# description = abstract(expinfo)
# )
# app <- prepareApp('rnaseq', eselist)
# shiny::shinyApp(ui = app$ui, server = app$server)
## ---- eval=FALSE--------------------------------------------------------------
# library(devtools)
# install_github('pinin4fjords/zhangneurons')
## ----eval=FALSE---------------------------------------------------------------
# library(shinyngs)
# data("zhangneurons")
## ----eval=FALSE---------------------------------------------------------------
# app <- prepareApp("rnaseq", zhangneurons)
# shiny::shinyApp(app$ui, app$server)
## ----eval=FALSE---------------------------------------------------------------
# app <- prepareApp("heatmap", zhangneurons)
# shiny::shinyApp(app$ui, app$server)
## ----eval=TRUE----------------------------------------------------------------
# Assays is a list of matrices
library(zhangneurons)
data(zhangneurons, envir = environment())
myassays <- as.list(SummarizedExperiment::assays(zhangneurons[[1]]))
head(myassays[[1]])
## ----eval=TRUE----------------------------------------------------------------
mycoldata <- data.frame(SummarizedExperiment::colData(zhangneurons[[1]]))
head(mycoldata)
## ----eval=TRUE----------------------------------------------------------------
myannotation <- SummarizedExperiment::mcols(zhangneurons[[1]])
head(myannotation)
## ----eval=TRUE----------------------------------------------------------------
myese <- ExploratorySummarizedExperiment(
assays = SimpleList(
myassays
),
colData = DataFrame(mycoldata),
annotation <- myannotation,
idfield = 'gene_id',
labelfield = "gene_name"
)
print(myese)
## ----eval=TRUE----------------------------------------------------------------
myesel <- ExploratorySummarizedExperimentList(
eses = list(expression = myese),
title = "My title",
author = "My Authors",
description = 'Look what I gone done'
)
## ----eval=FALSE---------------------------------------------------------------
# app <- prepareApp("rnaseq", myesel)
# shiny::shinyApp(app$ui, app$server)
## ----eval=TRUE----------------------------------------------------------------
myesel@group_vars <- c('Group', 'Tissue')
## ----eval=FALSE---------------------------------------------------------------
# app <- prepareApp("rnaseq", myesel)
# shiny::shinyApp(app$ui, app$server)
## ----eval=TRUE----------------------------------------------------------------
zhangneurons@contrasts
myesel@contrasts <- zhangneurons@contrasts
## ----eval=FALSE---------------------------------------------------------------
# app <- prepareApp("rnaseq", myesel)
# shiny::shinyApp(app$ui, app$server)
## ----eval=TRUE----------------------------------------------------------------
head(zhangneurons[[1]]@contrast_stats[[1]]$pvals, n = 10)
## ----eval=TRUE----------------------------------------------------------------
myesel[[1]]@contrast_stats <- zhangneurons[[1]]@contrast_stats
## ----eval=FALSE---------------------------------------------------------------
# app <- prepareApp("rnaseq", myesel)
# shiny::shinyApp(app$ui, app$server)
## ----eval=FALSE---------------------------------------------------------------
# genesets_files = list(
# 'KEGG' = "/path/to/MSigDB/c2.cp.kegg.v5.0.entrez.gmt",
# 'MSigDB canonical pathway' = "/path/to/MSigDB/c2.cp.v5.0.entrez.gmt",
# 'GO biological process' = "/path/to/MSigDB/c5.bp.v5.0.entrez.gmt",
# 'GO cellular component' = "/path/to/MSigDB/c5.cc.v5.0.entrez.gmt",
# 'GO molecular function' = "/path/to/MSigDB/c5.mf.v5.0.entrez.gmt",
# 'MSigDB hallmark'= "/path/to/MSigDB/h.all.v5.0.entrez.gmt"
# )
#
# gene_sets <- lapply(genesets_files, GSEABase::getGmt)
## ----eval = FALSE-------------------------------------------------------------
# myesel <- ExploratorySummarizedExperimentList(
# eses = list(expression = myese),
# title = "My title",
# author = "My Authors",
# description = 'Look what I gone done',
# gene_sets = gene_sets
# )
## ----eval = TRUE--------------------------------------------------------------
names(zhangneurons@gene_sets)
## ----eval = TRUE--------------------------------------------------------------
names(zhangneurons@gene_sets$gene_name$GOBP)[1:10]
## ----eval = TRUE--------------------------------------------------------------
zhangneurons@gene_sets$gene_name$GOBP$GO_LACTATE_TRANSPORT
## ----eval = TRUE--------------------------------------------------------------
names(zhangneurons$gene@gene_set_analyses)
names(zhangneurons$gene@gene_set_analyses$`Filtered normalised`)
names(zhangneurons$gene@gene_set_analyses$`Filtered normalised`$GOBP)
head(zhangneurons$gene@gene_set_analyses$`Filtered normalised`$GOBP$`MO-no-yes`)
## ----eval = FALSE-------------------------------------------------------------
# app <- prepareApp('dendro', eselist)
# shiny::shinyApp(ui = app$ui, server = app$server)
## ----eval = FALSE-------------------------------------------------------------
# ?shinyngs
## ----eval=FALSE---------------------------------------------------------------
# library(shinyngs)
#
# mydata <- readRDS("data.rds")
#
# app <- prepareApp("rnaseq", mydata)
# shiny::shinyApp(app$ui, app$server)
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