## ----eval=TRUE---------------------------------------------------------------- #select data library(octad) phenoDF=get_ExperimentHub_data("EH7274") #load data.frame with samples included in the OCTAD database. head(phenoDF) #list all data included within the package HCC_primary=subset(phenoDF,cancer=='liver hepatocellular carcinoma'&sample.type == 'primary') #select data case_id=HCC_primary$sample.id #select cases ## ----eval=TRUE---------------------------------------------------------------- #computing top 50 reference tissues control_id=computeRefTissue(case_id,output=FALSE,adjacent=TRUE,source = "octad",control_size = 50) #please note, if \code{output = TRUE}, \code{outputFolder} variable must be specified, otherwise it will be written to \code{tempdir()} # use adjacent normal tissue samples as control_id allow you to avoid running this function ## ----eval=TRUE---------------------------------------------------------------- #computing top 50 reference tissues control_id=subset(phenoDF,biopsy.site=='LIVER'&sample.type=='normal')$sample.id[1:50] #select first 50 samples from healthy liver # use adjacent normal tissue samples as control_id allow you to avoid running this function ## ----eval=TRUE---------------------------------------------------------------- tsne=get_ExperimentHub_data("EH7276") #Download file with tsneresults for all samples in the octad.db once. After this it will be cached and no additional download required. tsne$type <- "others" tsne$type[tsne$sample.id %in% case_id] <- "case" tsne$type[tsne$sample.id %in% control_id] <- "control" #plot p2 <- ggplot(tsne, aes(X, Y, color = type)) + geom_point(alpha = 0.4)+ labs(title = paste ('TNSE PLOT'), x= 'TSNE Dim1', y='TSNE Dim2', caption="OCTAD")+ theme_bw() p2 ## ----eval=FALSE--------------------------------------------------------------- # res=diffExp(case_id,control_id,source='octad.small',output=FALSE,DE_method='wilcox') # #please note, if \code{output = TRUE}, \code{outputFolder} variable must be specified, otherwise it will be written to \code{tempdir()} # head(res) # #Use simple subset to filter the DE results: # res=subset(res,abs(log2FoldChange)>1&padj<0.001) ## ----eval=FALSE--------------------------------------------------------------- # data("res_example") #load differential expression example for HCC vs adjacent liver tissue computed in diffExp() function from previous step # res=subset(res_example,abs(log2FoldChange)>1&padj<0.001) #load example expression dataset # sRGES=runsRGES(res,max_gene_size=100,permutations=1000,output=FALSE) # #please note, if \code{output = TRUE}, \code{outputFolder} variable must be specified, otherwise it will be written to \code{tempdir()} # head(sRGES) ## ----eval=TRUE---------------------------------------------------------------- cell_line_computed=computeCellLine(case_id=case_id,source='octad.small') #please note, if \code{output = TRUE}, \code{outputFolder} variable must be specified, otherwise it will be written to \code{tempdir()} head(cell_line_computed) ## ----eval=TRUE---------------------------------------------------------------- data("sRGES_example") #load example sRGES from octad.db #please note, if \code{outputFolder=NULL}, output it will be written to \code{tempdir()} topLineEval(topline = 'HEPG2',mysRGES = sRGES_example) ## ----eval=TRUE---------------------------------------------------------------- data("sRGES_example") octadDrugEnrichment(sRGES = sRGES_example, target_type='chembl_targets') #please note, if \code{outputFolder=NULL}, output it will be written to \code{tempdir()} ## ----eval=FALSE--------------------------------------------------------------- # get_ExperimentHub_data('EH7277') # res=diffExp(case_id,control_id,source='octad.whole', # output=FALSE,n_topGenes=10000,file='octad.counts.and.tpm.h5') ## ----eval=FALSE--------------------------------------------------------------- # data=data.table::fread(('https://ftp.ncbi.nlm.nih.gov/geo/series/GSE144nnn/GSE144269/suppl/GSE144269_RSEM_GeneCounts.txt.gz'),header=TRUE) # row.names(data)=data$entrez_id # data$entrez_id=NULL # samples=colnames(data) #define the case and control cohorts, A samples were obtained from tumors, B samples were obtained from adjacent tissue # case_id=samples[grepl('A_S',samples)] # control_id=samples[grepl('B_S',samples)] # res=diffExp(case_id,control_id,source='side',output=FALSE,outputFolder=tempdir(),n_topGenes=10000, # expSet=log2(as.matrix(data)+1),annotate=FALSE) #compute DE ## ----eval=TRUE---------------------------------------------------------------- sessionInfo()