## ----eval=FALSE--------------------------------------------------------------- # devtools::install_github("THERMOSTATS/RVA_prod") ## ----message=FALSE, warning=FALSE--------------------------------------------- library(RVA) ## ----setup, include=FALSE----------------------------------------------------- knitr::opts_chunk$set(echo = TRUE, rows.print=25, comment = "") options( ggplot2.continuous.colour = 'viridis', ggplot2.continuous.fill = 'viridis' ) ## ----------------------------------------------------------------------------- df <- RVA::Sample_summary_statistics_table df1 <- RVA::Sample_summary_statistics_table1 d1 <- list(df, df1) ## ---- echo=FALSE-------------------------------------------------------------- knitr::kable(head(d1[[1]])) ## ----eval=FALSE--------------------------------------------------------------- # plot_cutoff(data = data, # comp.names = NULL, # FCflag = "logFC", # FDRflag = "adj.P.Val", # FCmin = 1.2, # FCmax = 2, # FCstep = 0.1, # p.min = 0, # p.max = 0.2, # p.step = 0.01, # plot.save.to = NULL, # gen.3d.plot = TRUE, # gen.plot = TRUE) ## ----------------------------------------------------------------------------- cutoff.result <- plot_cutoff(data = df, gen.plot = TRUE, gen.3d.plot = TRUE) ## ---- eval=FALSE-------------------------------------------------------------- # head(cutoff.result[[1]]) ## ---- echo= FALSE------------------------------------------------------------- knitr::kable(head(cutoff.result[[1]])) ## ---- warning=FALSE, eval=FALSE----------------------------------------------- # cutoff.result[[2]] ## ---- warning=FALSE----------------------------------------------------------- cutoff.result[[3]] ## ---- eval=FALSE-------------------------------------------------------------- # plot_cutoff(data = df, # plot.save.to = "cut_off_selection_plot.png") ## ---- eval=FALSE-------------------------------------------------------------- # library(ggplot2) # ggsave("cut_off_selection_plot.png", cutoff.result[[3]], width = 5, height = 5, dpi = 300) ## ---- message=FALSE----------------------------------------------------------- cutoff.result.list <- plot_cutoff(data = d1, comp.names = c('a', 'b')) ## ---- eval=FALSE-------------------------------------------------------------- # head(cutoff.result.list[[1]]) ## ---- echo=FALSE-------------------------------------------------------------- knitr::kable(head(cutoff.result.list[[1]])) ## ----------------------------------------------------------------------------- cutoff.result.list ## ---- eval=FALSE-------------------------------------------------------------- # plot_cutoff(data = d1, # comp.names = c("A", "B"), # plot.save.to = "cut_off_list_plot.png") ## ---- eval=FALSE-------------------------------------------------------------- # library(ggplot2) # ggsave("cut_off_list_plot.png", cutoff.result.list, width = 5, height = 5, dpi = 300) ## ---- results='hide'---------------------------------------------------------- qq.result <- plot_qq(df) qq.result ## ---- eval=FALSE-------------------------------------------------------------- # plot_qq(data = df, # plot.save.to = "qq_plot.png") ## ---- eval=FALSE-------------------------------------------------------------- # library(ggplot2) # ggsave("qq_plot.png", qq.result, width = 5, height = 5, dpi = 300) ## ---- results='hide'---------------------------------------------------------- qq.list.result <- plot_qq(data = d1, comp.names = c('A', 'B')) qq.list.result ## ---- eval=FALSE-------------------------------------------------------------- # plot_qq(data = d1, # comp.names = c("A", "B"), # plot.save.to = "qq_list_plot.png") ## ---- eval=FALSE-------------------------------------------------------------- # library(ggplot2) # ggsave("qq_list_plot.png", qq.list.result, width = 5, height = 5, dpi = 300) ## ----eval=FALSE--------------------------------------------------------------- # plot_volcano( # data = data, # comp.names = NULL, # geneset = NULL, # geneset.FCflag = "logFC", # highlight.1 = NULL, # highlight.2 = NULL, # upcolor = "#FF0000", # downcolor = "#0000FF", # plot.save.to = NULL, # xlim = c(-4, 4), # ylim = c(0, 12), # FCflag = "logFC", # FDRflag = "adj.P.Val", # highlight.FC.cutoff = 1.5, # highlight.FDR.cutoff = 0.05, # title = "Volcano plot", # xlab = "log2 Fold Change", # ylab = "log10(FDR)" # ) ## ----message=FALSE, results='hide', warning=FALSE----------------------------- plot_volcano(data = df) ## ----message=FALSE, results='hide', warning=FALSE----------------------------- plot_volcano(data = d1, comp.names = c('a', 'b')) ## ----------------------------------------------------------------------------- #disease gene set used to color volcanoplot dgs <- RVA::Sample_disease_gene_set ## ----eval=FALSE--------------------------------------------------------------- # head(dgs) ## ----echo=FALSE--------------------------------------------------------------- knitr::kable(head(dgs)) ## ----message=FALSE,warning=FALSE---------------------------------------------- plot_volcano(data = df, geneset = dgs, upcolor = "#FF0000", downcolor = "#0000FF", xlim = c(-3,3), ylim = c(0,14)) ## ----message=FALSE, warning=FALSE--------------------------------------------- plot_volcano(data = d1, comp.names = c('a', 'b'), geneset = dgs, upcolor = "#FF0000", downcolor = "#0000FF", xlim = c(-3,3), ylim = c(0,14)) ## ----message=FALSE,warning=FALSE---------------------------------------------- volcano.result <- plot_volcano(data = df, highlight.1 = c("ENSG00000169031.19","ENSG00000197385.5","ENSG00000111291.8"), highlight.2 = c("ENSG00000123610.5","ENSG00000120217.14", "ENSG00000138646.9", "ENSG00000119922.10","ENSG00000185745.10"), upcolor = "darkred", downcolor = "darkblue", xlim = c(-3,3), ylim = c(0,14)) volcano.result ## ---- warning=FALSE, eval=FALSE----------------------------------------------- # plot_volcano(data = df, # geneset = dgs, # plot.save.to = "volcano_plot.png") ## ---- eval=FALSE-------------------------------------------------------------- # library(ggplot2) # ggsave("volcano_plot.png", volcano.result, width = 5, height = 5, dpi = 300) ## ----eval=FALSE--------------------------------------------------------------- # plot_pathway( # data = df, # comp.names = NULL, # gene.id.type = "ENSEMBL", # FC.cutoff = 1.3, # FDR.cutoff = 0.05, # FCflag = "logFC", # FDRflag = "adj.P.Val", # Fisher.cutoff = 0.1, # Fisher.up.cutoff = 0.1, # Fisher.down.cutoff = 0.1, # plot.save.to = NULL, # pathway.db = "rWikiPathways" # ) ## ----message=FALSE, warning=FALSE, results="hide"----------------------------- pathway.result <- plot_pathway(data = df, pathway.db = "Hallmark", gene.id.type = "ENSEMBL") ## ----eval=FALSE--------------------------------------------------------------- # head(pathway.result[[1]]) ## ----echo=FALSE--------------------------------------------------------------- knitr::kable(head(pathway.result[[1]])) ## ----eval=FALSE--------------------------------------------------------------- # head(pathway.result[[2]]) ## ----echo=FALSE--------------------------------------------------------------- knitr::kable(head(pathway.result[[2]])) ## ----------------------------------------------------------------------------- pathway.result[[3]] ## ----------------------------------------------------------------------------- pathway.result[[4]] ## ----------------------------------------------------------------------------- pathway.result[[5]] ## ----eval=FALSE--------------------------------------------------------------- # library(ggplot2) # ggsave("joint_plot.png",pathway.result[[5]], width = 5, height = 5, dpi = 300) ## ----message=FALSE, warning=FALSE, results="hide"----------------------------- list.pathway.result <- plot_pathway(data = list(df,df1),comp.names=c("A","B"),pathway.db = "Hallmark", gene.id.type = "ENSEMBL") ## ----eval=FALSE--------------------------------------------------------------- # head(list.pathway.result[[1]]) ## ----echo=FALSE--------------------------------------------------------------- knitr::kable(head(list.pathway.result[[1]])) ## ----eval=FALSE--------------------------------------------------------------- # head(list.pathway.result[[2]]) ## ----echo=FALSE--------------------------------------------------------------- knitr::kable(head(list.pathway.result[[2]])) ## ----------------------------------------------------------------------------- list.pathway.result[[3]] ## ----------------------------------------------------------------------------- list.pathway.result[[4]] ## ---- eval=FALSE-------------------------------------------------------------- # library(ggplot2) # ggsave("non-directional.png",pathway.result[[4]], width = 5, height = 5, dpi = 300) ## ----------------------------------------------------------------------------- count <- RVA::count_table[,1:50] ## ---- eval=FALSE-------------------------------------------------------------- # count[1:6,1:5] ## ----echo=FALSE--------------------------------------------------------------- knitr::kable(count[1:6,1:5]) ## ----------------------------------------------------------------------------- annot <- RVA::sample_annotation[1:50,] ## ----eval=FALSE--------------------------------------------------------------- # head(annot) ## ----echo=FALSE--------------------------------------------------------------- knitr::kable(head(annot)) ## ----message=FALSE------------------------------------------------------------ hm.expr <- plot_heatmap.expr(data = count, annot = annot, sample.id = "sample_id", annot.flags = c("day", "Treatment"), ct.table.id.type = "ENSEMBL", gene.id.type = "SYMBOL", gene.names = NULL, gene.count = 10, title = "RVA Heatmap", fill = "CPM", baseline.flag = "day", baseline.val = "0", plot.save.to = NULL, input.type = "count") ## ---- echo=FALSE-------------------------------------------------------------- hm.expr[[1]] ## ---- eval=FALSE-------------------------------------------------------------- # head(hm.expr[[2]]) ## ---- echo=FALSE-------------------------------------------------------------- knitr::kable(head(hm.expr[[2]])) ## ----results='hide', eval=FALSE----------------------------------------------- # library(ComplexHeatmap) # png("heatmap_plots2cp.png", width = 500, height = 500) # draw(hm.expr$gp) # dev.off() # ## ----message=FALSE------------------------------------------------------------ hm.expr.cfb <- plot_heatmap.expr(data = count, annot = annot, sample.id = "sample_id", annot.flags = c("day", "Treatment"), ct.table.id.type = "ENSEMBL", gene.id.type = "SYMBOL", gene.names = NULL, gene.count = 10, title = "RVA Heatmap", fill = "CFB", baseline.flag = "day", baseline.val = "0", plot.save.to = NULL, input.type = "count") ## ---- echo=FALSE-------------------------------------------------------------- hm.expr.cfb[[1]] ## ---- eval=FALSE-------------------------------------------------------------- # head(hm.expr.cfb[[2]]) ## ---- echo=FALSE-------------------------------------------------------------- knitr::kable(head(hm.expr.cfb[[2]])) ## ----results='hide', eval=FALSE----------------------------------------------- # library(ComplexHeatmap) # png("heatmap_plots1cf.png", width = 500, height = 500) # draw(hm.expr.cfb$gp) # dev.off() ## ----------------------------------------------------------------------------- anno <- RVA::sample_annotation ## ---- eval=FALSE-------------------------------------------------------------- # head(anno) ## ---- echo=FALSE-------------------------------------------------------------- knitr::kable(head(anno)) ## ----------------------------------------------------------------------------- ct <- RVA::sample_count_cpm ## ----eval=FALSE--------------------------------------------------------------- # ct[1:6,1:5] ## ----echo=FALSE--------------------------------------------------------------- knitr::kable(ct[1:6,1:5]) ## ----------------------------------------------------------------------------- gene.result <- plot_gene(ct, anno, gene.names = c("AAAS", "A2ML1", "AADACL3", "AARS"), ct.table.id.type = "ENSEMBL", gene.id.type = "SYMBOL", treatment = "Treatment", sample.id = "sample_id", time = "day", log.option = TRUE, plot.save.to = NULL, input.type = "cpm") ## ---- echo = FALSE------------------------------------------------------------ gene.result[[1]] ## ---- eval = FALSE------------------------------------------------------------ # head(gene.result[[2]]) ## ---- echo = FALSE------------------------------------------------------------ knitr::kable(head(gene.result[[2]])) ## ----message=FALSE, eval=FALSE------------------------------------------------ # library(ggplot2) # ggsave(gene.result, "gene_plots1_4.png", device = "png", width = 100, height = 100, dpi = 200, limitsize = FALSE)