## ----loadup, echo=FALSE------------------------------------------------------- suppressPackageStartupMessages({ library(SummarizedExperiment) library(ivygapSE) library(DT) library(grid) library(png) library(ggplot2) library(limma) library(randomForest) }) ## ----chk---------------------------------------------------------------------- library(ivygapSE) data(ivySE) ivySE ## ----lkd---------------------------------------------------------------------- dim(ivySE) ## ----lkse--------------------------------------------------------------------- length(unique(metadata(ivySE)$tumorDetails$donor_id)) ## ----lkcon-------------------------------------------------------------------- sum(metadata(ivySE)$tumorDetails$tumor_name %in% ivySE$tumor_name) ## ----getsbd,echo=FALSE-------------------------------------------------------- subd = metadata(ivySE)$subBlockDetails dsub = dim(subd) ## ----lkonto,image=TRUE,echo=FALSE--------------------------------------------- nomenclat() ## ----lkk,echo=FALSE,fig=TRUE-------------------------------------------------- designOverview() ## ----lkdttum,echo=FALSE------------------------------------------------------- datatable(tumorDetails(ivySE), options=list(lengthMenu=c(3,5,10,50,100))) ## ----lkdts,echo=FALSE--------------------------------------------------------- datatable(subBlockDetails(ivySE), options=list(lengthMenu=c(3,5,10,50, 100))) ## ----lkcdd,echo=FALSE--------------------------------------------------------- datatable(as.data.frame(colData(ivySE)), options=list(lengthMenu=c(3,5,10,50,100))) ## ----lksbbbb------------------------------------------------------------------ sb = subBlockDetails(ivySE) table(sb$study_name) ## ----lksa,fig=TRUE------------------------------------------------------------ struc = as.character(colData(ivySE)$structure_acronym) spls = strsplit(struc, "-") basis = vapply(spls, function(x) x[1], character(1)) spec = vapply(spls, function(x) x[2], character(1)) table(basis, exclude=NULL) barplot(table(basis)) ## ----lktab-------------------------------------------------------------------- lapply(split(spec,basis), function(x)sort(table(x),decreasing=TRUE)) ## ----lklim, cache=TRUE-------------------------------------------------------- library(limma) ebout = getRefLimma() ## ----lknnn-------------------------------------------------------------------- odig = options()$digits options(digits=3) limma::topTable(ebout, 2) options(digits=odig) # revert ## ----bindmol------------------------------------------------------------------ moltype = tumorDetails(ivySE)$molecular_subtype names(moltype) = tumorDetails(ivySE)$tumor_name moltype[nchar(moltype)==0] = "missing" ivySE$moltype = factor(moltype[ivySE$tumor_name]) ## ----setdup, cache=TRUE------------------------------------------------------- library(limma) refex = ivySE[, grep("reference", ivySE$structure_acronym)] refmat = assay(refex) tydes = model.matrix(~moltype, data=as.data.frame(colData(refex))) ok = which(apply(tydes,2,sum)>0) # some subtypes don't have ref histo samples tydes = tydes[,ok] block = factor(refex$tumor_id) dd = duplicateCorrelation(refmat, tydes, block=block) f2 = lmFit(refmat, tydes, correlation=dd$consensus) ef2 = eBayes(f2) colnames(tydes) topTable(ef2,2) ## ----lkrf,fig=TRUE------------------------------------------------------------ refex = ivySE[, grep("reference", ivySE$structure_acronym)] refex$struc = factor(refex$structure_acronym) iqrs = rowIQRs(assay(refex)) inds = which(iqrs>quantile(iqrs,.5)) set.seed(1234) rf1 = randomForest(x=t(assay(refex[inds,])), y=refex$struc, mtry=30, importance=TRUE) rf1 varImpPlot(rf1)