Nothing
## ---- message=FALSE-----------------------------------------------------------
library(crossmeta)
# specify where data will be downloaded
data_dir <- file.path(getwd(), "data", "LY")
# gather all GSEs
gse_names <- c("GSE9601", "GSE15069", "GSE50841", "GSE34817", "GSE29689")
# gather Illumina GSEs (see 'Checking Raw Illumina Data')
illum_names <- c("GSE50841", "GSE34817", "GSE29689")
# download raw data
# get_raw(gse_names, data_dir)
## ---- eval=FALSE--------------------------------------------------------------
# # this is why we gathered Illumina GSEs
# open_raw_illum(illum_names, data_dir)
## ---- message=FALSE, warning=FALSE--------------------------------------------
library(lydata)
# location of raw data
data_dir <- system.file("extdata", package = "lydata")
## ---- message=FALSE, warning=FALSE, results='hide'----------------------------
# reloads if previously called
esets <- load_raw(gse_names, data_dir)
## ---- eval=FALSE--------------------------------------------------------------
# library(Biobase)
# library(AnnotationDbi)
#
# # check feature data to see what columns are available
# head(fData(esets$GSE15069))
#
# # if using RStudio
# # View(fData(esets$GSE15069))
#
# # annotation package for appropriate species
# library(org.Mm.eg.db)
#
# # map from accession number to entrez gene ids
# acnums <- as.character(fData(esets$GSE15069)$GB_ACC)
# enids <- mapIds(org.Mm.eg.db, acnums, "ENTREZID", "ACCNUM")
#
# # add 'GENE_ID' column with entrez ids
# fData(esets$GSE15069)$GENE_ID <- enids
#
# # use crossmeta to map from entrez gene ids to homologous hgnc symbol
# esets$GSE15069 <- symbol_annot(esets$GSE15069)
#
# # to overwrite saved eset (to avoid repeating above)
# saveRDS(esets$GSE15069, file.path(data_dir, "GSE15069", "GSE15069_eset.rds"))
## ---- eval=FALSE--------------------------------------------------------------
# anals <- diff_expr(esets, data_dir)
## -----------------------------------------------------------------------------
# load auto-saved results of previous call to diff_expr
prev <- load_diff(gse_names, data_dir)
# supply prev to diff_expr
# anals <- diff_expr(esets, data_dir, prev_anals=prev)
## ---- message=FALSE, warning=FALSE, results='hide', fig.keep='none'-----------
library(Biobase)
# load eset
gse_name <- c("GSE34817")
eset <- load_raw(gse_name, data_dir)
# inspect pData of eset
# View(pData(eset$GSE34817)) # if using RStudio
head(pData(eset$GSE34817)) # otherwise
# get group info from pData (differs based on eset)
group <- pData(eset$GSE34817)$characteristics_ch1.1
# make group names concise and valid
group <- gsub("treatment: ", "", group)
group <- make.names(group)
# add group to eset pData
pData(eset$GSE34817)$group <- group
# setup selections
sel <- setup_prev(eset, contrasts = "LY-DMSO")
# run differential expression analysis
# anal <- diff_expr(eset, data_dir, prev_anal = sel)
## ---- message=FALSE, results='hide'-------------------------------------------
# run GUI to add tissue sources
# anals <- add_sources(prev, data_dir)
# for usage details
?add_sources
## ---- message=FALSE, results='hide'-------------------------------------------
# re-load previous analyses if need to
anals <- load_diff(gse_names, data_dir)
# perform meta analyses by tissue source
es_res <- es_meta(anals, by_source = TRUE)
# for explanation of values
?es_meta
## -----------------------------------------------------------------------------
sessionInfo()
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