## ---- include = FALSE--------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----show data1,echo=FALSE, results='asis', booktabs = TRUE------------------- knitr::kable( head(PEIMAN2::exmplData1$pl1), col.names = '', caption = '') knitr::kable( head(PEIMAN2::exmplData1$pl2), col.names = '', caption = '') ## ----show data2,echo=FALSE, results='asis'------------------------------------ knitr::kable(PEIMAN2::exmplData2[1:6,], caption='beatAML dataset samples') ## ----------------------------------------------------------------------------- # Load PEIMAN2 package library(PEIMAN2) # Extract dataset and assign a variable name to it pl1 <- exmplData1$pl1 # Run SEA on the list enrich1 <- runEnrichment(protein = pl1, os.name = 'Homo sapiens (Human)') ## ----echo = FALSE------------------------------------------------------------- knitr::kable( head(enrich1), format = 'html') ## ----------------------------------------------------------------------------- getTaxonomyName(x = exmplData1$pl1) ## ----------------------------------------------------------------------------- # Extract dataset and assign a variable name to it pl2 <- exmplData1$pl2 # Run SEA on the list enrich2 <- runEnrichment(protein = pl2, os.name = 'Homo sapiens (Human)') ## ----echo = FALSE------------------------------------------------------------- knitr::kable( head(enrich2), format = 'html') ## ----fig.dim = c(8, 6)-------------------------------------------------------- plotEnrichment(x = enrich1, sig.level = 0.05) ## ----fig.dim = c(8,6)--------------------------------------------------------- plotEnrichment(x = enrich1, y = enrich2, sig.level = 0.05) ## ----------------------------------------------------------------------------- psea_res <- runPSEA(protein = exmplData2, os.name = 'Rattus norvegicus (Rat)', nperm = 1000) ## ----------------------------------------------------------------------------- knitr::kable(psea_res[[1]], format = 'html') ## ----fig.width=14, fig.height=12, fig.align='center'-------------------------- plotPSEA(x = psea_res) ## ----echo = FALSE, fig.width=12, fig.height=12-------------------------------- plotRunningScore(x = psea_res) ## ----------------------------------------------------------------------------- MS <- psea2mass(x = psea_res, sig.level = 0.05) MS