if (!require("magrittr", character.only = TRUE)) {
BiocManager::install("magrittr")
require("magrittr", character.only = TRUE)
}
source("data-raw/UtilityFunctionForCuration.R")
##### Read in raw data #####
geo <- "GSE42832"
sequencePlatform <- "GPL10558"
GSE42832_data_list <- readRawData(geo, sequencePlatform)
GSE42832_Non_normalized_data <- GSE42832_Non_pvalue <- GSE42832_data_list$data_Non_normalized
gse <- GEOquery::getGEO(geo, GSEMatrix = FALSE)
colnames(GSE42832_Non_pvalue) <- colnames(GSE42832_Non_normalized_data) <-
names(GEOquery::GSMList(gse))
##### Create column data #####
characteristic_data_frame <- readRawColData(gse)
colnames(characteristic_data_frame) <- c("TBStatus", "Tissue")
TBStatus <- TBStatus_temp <- as.character(characteristic_data_frame$TBStatus)
unique(TBStatus_temp)
for(i in 1:length(TBStatus)){
if(TBStatus_temp[i] == "TB"){
TBStatus[i] <- "PTB"
}
if(TBStatus_temp[i] == "Sarcoid"){
TBStatus[i] <- "OD"
}
}
characteristic_data_frame$TBStatus <- TBStatus
Tissue <- Tissue_temp <- as.character(characteristic_data_frame$Tissue)
Tissue[grep("whole blood", Tissue_temp)] <- "Whole Blood"
characteristic_data_frame$Tissue <- Tissue
SarcoidosisStatus <- rep("Negative", nrow(characteristic_data_frame))
SarcoidosisStatus[grep("Sarcoid", TBStatus_temp)] <- "Positive"
characteristic_data_frame$SarcoidosisStatus <- SarcoidosisStatus
col_info <- create_standard_coldata(characteristic_data_frame)
new_col_info <- S4Vectors::DataFrame(col_info)
##### Create row data #####
row_data <- map_gene_symbol(GSE42832_Non_pvalue, sequencePlatform)
new_row_data <- match_gene_symbol(row_data)
##### Create meta data #####
GSE42832_experimentData <- methods::new("MIAME",
name = "Chole Bloom",
lab = "MRC National Institute for Medical Research",
contact = "cbloom@nimr.mrc.ac.uk",
title = "Transcriptional blood signatures distinguish pulmonary tuberculosis, pulmonary sarcoidosis, pneumonias and lung cancers.",
abstract = "An Interferon-inducible neutrophil-driven blood transcriptional signature was present in both sarcoidosis and tuberculosis, with a higher abundance and expression in tuberculosis.
Heterogeneity of the sarcoidosis signature correlated significantly with disease activity.
Transcriptional profiles in pneumonia and lung cancer revealed an over-abundance of inflammatory transcripts. After successful treatment the transcriptional activity in tuberculosis and pneumonia patients was significantly reduced.
However the glucocorticoid-responsive sarcoidosis patients showed a significant increase in transcriptional activity.
144-blood transcripts were able to distinguish tuberculosis from other lung diseases and controls.",
url = "10.1371/journal.pone.0070630",
pubMedIds = "23940611",
other = list(Platform = "Illumina HumanHT-12 V4.0 expression beadchip (GPL10558)"))
GSE42832_sobject <- SummarizedExperiment::SummarizedExperiment(
assays = list(GSE42832_Non_normalized_data = as.matrix(GSE42832_Non_normalized_data)),
colData = new_col_info,
rowData = new_row_data,
metadata = list(GSE42832_experimentData));GSE42832_sobject
save_raw_files(GSE42832_sobject, path = "data-raw/", geo = geo)
##### Create normalized curated assay #####
GSE42832_normed <- GSE42832_data_list$data_normalized
colnames(GSE42832_normed) <- names(GEOquery::GSMList(gse))
curatedExprs <- probesetsToGenes(row_data = new_row_data,
data_normalized = GSE42832_normed,
FUN = median)
saveRDS(curatedExprs, paste0("data-raw/", geo, "_assay_curated.RDS"))
unlink(paste0(normalizePath(tempdir()), "/", dir(tempdir())), recursive = TRUE)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.