## ----style-knitr, eval=TRUE, echo=FALSE, results="asis"-------------------- BiocStyle::latex() ## ----setup, echo=FALSE----------------------------------------------------- knitr::opts_chunk$set(message=FALSE, fig.align="center", comment="") ## ----echo=FALSE------------------------------------------------------------ x <- citation("missRows") ## ----eval=FALSE------------------------------------------------------------ # help("MIMFA") ## ----eval=FALSE------------------------------------------------------------ # ?MIMFA ## ----quickStart, eval=FALSE------------------------------------------------ # ## Data preparation # midt <- MIDTList(table1, table2, colData=df) # # ## Performing MI # midt <- MIMFA(midt, ncomp=2, M=30) # # ## Analysis of the results - Visualization # plotInd(midt) # plotVar(midt) ## ----eval=FALSE------------------------------------------------------------ # if (!requireNamespace("BiocManager", quietly=TRUE)) # install.packages("BiocManager") # BiocManager::install() ## ----install, eval=FALSE--------------------------------------------------- # if (!requireNamespace("BiocManager", quietly=TRUE)) # install.packages("BiocManager") # BiocManager::install("missRows") ## ----loadLibrary, message=FALSE, warning=FALSE----------------------------- library(missRows) ## ----searchHelp, eval=FALSE------------------------------------------------ # help.search("missRows") ## ----loadData-------------------------------------------------------------- data(NCI60) ## -------------------------------------------------------------------------- names(NCI60) ## -------------------------------------------------------------------------- table(NCI60$dataTables$cell.line$type) ## -------------------------------------------------------------------------- NCI60$mae ## -------------------------------------------------------------------------- data(NCI60) ## ----dirMIDTList----------------------------------------------------------- tableList <- NCI60$dataTables[1:2] cell.line <- NCI60$dataTables$cell.line midt <- MIDTList(tableList, colData=cell.line, assayNames=c("trans", "prote")) ## ----sepMIDTList----------------------------------------------------------- table1 <- NCI60$dataTables$trans table2 <- NCI60$dataTables$prote cell.line <- NCI60$dataTables$cell.line midt <- MIDTList(table1, table2, colData=cell.line, assayNames=c("trans", "prote")) ## ----sepMIDTList2---------------------------------------------------------- midt <- MIDTList("trans" = table1, "prote" = table2, colData=cell.line) ## ----maeMIDTList----------------------------------------------------------- midt <- MIDTList(NCI60$mae) ## -------------------------------------------------------------------------- midt ## ----MIMFA, echo=2--------------------------------------------------------- set.seed(123) midt <- MIMFA(midt, ncomp=50, M=30, estimeNC=TRUE) ## -------------------------------------------------------------------------- midt ## -------------------------------------------------------------------------- names(midt) ## -------------------------------------------------------------------------- cell.line <- colData(midt) ## ----MthConf--------------------------------------------------------------- conf <- configurations(midt, M=5) dim(conf) ## ----missingPattern, fig.width=6, fig.height=5, out.width="0.6\\textwidth"---- patt <- missPattern(midt, colMissing="grey70") ## ----missingPatternMat----------------------------------------------------- patt ## ----plotInd, fig.width=6, fig.height=5, out.width="0.55\\textwidth"------- plotInd(midt, colMissing="white") ## ----plotInd-ellipses, fig.width=6, fig.height=5, out.width="0.55\\textwidth"---- plotInd(midt, confAreas="ellipse", confLevel=0.95) ## ----plotInd-convexhull, fig.width=6, fig.height=5, out.width="0.55\\textwidth"---- plotInd(midt, confAreas="convex.hull") ## ----plotVar, fig.width=6, fig.height=5, out.width="0.55\\textwidth"------- plotVar(midt, radIn=0.5) ## ----plotVar-cutoff, fig.width=6, fig.height=5, out.width="0.55\\textwidth"---- plotVar(midt, radIn=0.55, varNames=TRUE, cutoff=0.55) ## ----tuneM, echo=FALSE----------------------------------------------------- set.seed(1) tune <- tuneM(midt, ncomp=2, Mmax=100, inc=10, N=20, showPlot=FALSE) ## ----eval=FALSE------------------------------------------------------------ # tune <- tuneM(midt, ncomp=2, Mmax=100, inc=10, N=20) # tune ## -------------------------------------------------------------------------- tune$stats ## ----echo=FALSE, fig.width=6.5, fig.height=5, out.width="0.5\\textwidth"---- tune$ggp ## ----session-info, echo=FALSE---------------------------------------------- sessionInfo()