@@ -464,8 +464,7 @@ get_y_init <- function(df, y_delta, pseudocount){
464464# '
465465# ' @return final carnation object with additional pre-processing
466466# '
467- # ' @examples
468- # ' \donttest{
467+ # ' @examplesIf interactive()
469468# ' library(DESeq2)
470469# '
471470# ' # make example DESeq dataset
@@ -495,7 +494,6 @@ get_y_init <- function(df, y_delta, pseudocount){
495494# '
496495# ' # final object
497496# ' final_obj <- make_final_object(obj)
498- # ' }
499497# '
500498# ' @export
501499make_final_object <- function (obj ){
@@ -853,10 +851,22 @@ enrich_to_genetonic <- function(enrich, res){
853851# ' @return ggplot handle
854852# '
855853# ' @examples
856- # ' # get DE results
857- # ' data(res_dex, package='carnation')
854+ # ' library(DESeq2)
855+ # '
856+ # ' # make example DESeq dataset
857+ # ' dds <- makeExampleDESeqDataSet()
858+ # '
859+ # ' # run DE analysis
860+ # ' dds <- DESeq(dds)
861+ # '
862+ # ' # extract comparison of interest
863+ # ' res <- results(dds, contrast = c("condition", "A", "B"))
864+ # '
865+ # ' # add gene and symbol column
866+ # ' res$gene <- rownames(res)
867+ # ' res$symbol <- rownames(res)
858868# '
859- # ' plotMA.label(res_dex , lab.genes = c("SPARCL1 ", "CACNB2 "))
869+ # ' plotMA.label(res , lab.genes = c("gene1 ", "gene2 "))
860870# '
861871# ' @export
862872plotMA.label <- function (res ,
@@ -1037,11 +1047,22 @@ add.set.column <- function(df){
10371047# ' @return plotly handle
10381048# '
10391049# ' @examples
1040- # ' # get DE results
1041- # ' data(res_dex, package='carnation')
1050+ # ' library(DESeq2)
1051+ # '
1052+ # ' # make example DESeq dataset
1053+ # ' dds <- makeExampleDESeqDataSet()
1054+ # '
1055+ # ' # run DE analysis
1056+ # ' dds <- DESeq(dds)
1057+ # '
1058+ # ' # extract comparison of interest
1059+ # ' res <- results(dds, contrast = c("condition", "A", "B"))
1060+ # '
1061+ # ' # add gene and symbol column
1062+ # ' res$gene <- rownames(res)
1063+ # ' res$symbol <- rownames(res)
10421064# '
1043- # ' # generate interactive MA plot
1044- # ' plotMA.label_ly(res_dex, lab.genes = c("SPARCL1", "CACNB2"))
1065+ # ' plotMA.label(res, lab.genes = c("gene1", "gene2"))
10451066# '
10461067# ' @export
10471068plotMA.label_ly <- function (res ,
@@ -2273,11 +2294,17 @@ makeEnrichResult <- function(df, split='/',
22732294# ' @return ggplot handle
22742295# '
22752296# ' @examples
2297+ # ' library(DESeq2)
2298+ # '
2299+ # ' # make example dataset
2300+ # ' dds <- makeExampleDESeqDataSet()
2301+ # '
2302+ # ' # run DE analysis
2303+ # ' dds <- DESeq(dds)
2304+ # '
22762305# ' # extract comparisons of interest
2277- # ' data(res_dex, package='carnation')
2278- # ' data(res_cell, package='carnation')
2279- # ' res1 <- res_dex
2280- # ' res2 <- res_cell
2306+ # ' res1 <- results(dds, contrast = c("condition", "A", "B"))
2307+ # ' res2 <- results(dds, contrast = c("condition", "B", "A"))
22812308# '
22822309# ' # add geneid column
22832310# ' res1 <- cbind(geneid=rownames(res1), res1)
@@ -2433,11 +2460,17 @@ plotScatter.label <- function(compare,
24332460# ' @return plotly handle
24342461# '
24352462# ' @examples
2463+ # ' library(DESeq2)
2464+ # '
2465+ # ' # make example dataset
2466+ # ' dds <- makeExampleDESeqDataSet()
2467+ # '
2468+ # ' # run DE analysis
2469+ # ' dds <- DESeq(dds)
2470+ # '
24362471# ' # extract comparisons of interest
2437- # ' data(res_dex, package='carnation')
2438- # ' data(res_cell, package='carnation')
2439- # ' res1 <- res_dex
2440- # ' res2 <- res_cell
2472+ # ' res1 <- results(dds, contrast = c("condition", "A", "B"))
2473+ # ' res2 <- results(dds, contrast = c("condition", "B", "A"))
24412474# '
24422475# ' # add geneid column
24432476# ' res1 <- cbind(geneid=rownames(res1), res1)
@@ -2664,10 +2697,8 @@ dummy_genetonic <- function(eres){
26642697# '
26652698# ' @return reactiveValues object containing carnation object
26662699# '
2667- # ' @examples
2668- # ' \donttest{
2700+ # ' @examplesIf interactive()
26692701# ' obj <- make_example_carnation_object()
2670- # ' }
26712702# '
26722703# ' @export
26732704make_example_carnation_object <- function (){
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