Add travis, tests, coverage, more docs

.Rbuildignore

@@ -4,3 +4,4 @@
 ^README-.*\.png$
 ^data-raw$
 ^docs$
+^codecov\.yml$

.travis.yml

@@ -0,0 +1,8 @@
+language: r
+cache: packages
+
+r_github_packages:
+  - r-lib/covr
+
+after_success:
+  - Rscript -e 'covr::codecov()'

DESCRIPTION

@@ -18,14 +18,15 @@ Imports:
     colorspace,
     magrittr,
     htmlwidgets
-Suggests: 
+Suggests:
     knitr,
     testthat,
     rmarkdown,
     TCGAbiolinks,
     gdata,
     SummarizedExperiment,
     edgeR,
-    pkgdown
+    pkgdown,
+    covr
 VignetteBuilder: knitr
 RoxygenNote: 6.0.1.9000

Makefile

@@ -14,3 +14,6 @@ document:
 
 install:
 	R --no-save --slave -e 'devtools::install()'
+
+test:
+	R --no-save --slave -e 'devtools::test()'

R/basic.R → R/boxplot.R

@@ -1,3 +1,10 @@
+#' A boxplot with jittered points
+#' @param x A data.frame
+#' @param box_hoverinfo Show hoverinfo for the boxplot trace? (logical)
+#' @param colors The colors to be used for the x-axis groups
+#' @return A plotly object
+#' @examples
+#'  plotly_boxplot(iris[, -5])
 #' @export
 plotly_boxplot <- function(x,
         box_hoverinfo = FALSE,

R/lineplot.R

@@ -1,17 +1,28 @@
 ## https://stackoverflow.com/questions/48096600/can-i-make-a-line-plot-with-a-dropdown-menu-in-r-without-using-shiny-or-plotly/
+#' A line plot with selectable y variables
+#' @param df A data.frame
+#' @param x The column name (as a string) of the x variable
+#' @param yvars The column names (as strings) to be used as y variables
+#' @return A plotly object
+#' @examples
+#' set.seed(42)
+#' df <- lapply(1:26, function(x) rnorm(50)) %>%
+#'     as.data.frame()
+#' colnames(df) <- letters
+#' df[["seq"]] <- 1:50
+#' df %>% dropdown_lineplot(x="seq", yvars = letters)
 #' @export
-dropdown_lineplot <- function(df, x) {
+dropdown_lineplot <- function(df, x, yvars) {
     ## Add trace directly here, since plotly adds a blank trace otherwise
-    cols <- setdiff(colnames(df), x)
     p <- plot_ly(
         type = "scatter",
         mode = "lines",
         x = ~ df[[x]],
-        y = ~ df[[cols[[1]]]],
-        name = cols[[1]])
+        y = ~ df[[yvars[[1]]]],
+        name = yvars[[1]])
     ## Add arbitrary number of traces
     ## Ignore first col as it has already been added
-    for (col in cols[-1]) {
+    for (col in yvars[-1]) {
         p <- p %>% add_lines(
           x = ~ df[[x]],
           y = df[[col]],
@@ -28,9 +39,9 @@ dropdown_lineplot <- function(df, x) {
             list(
                 y = 0.7,
                 ## Add all buttons at once
-                buttons = lapply(cols, function(col) {
+                buttons = lapply(yvars, function(col) {
                   list(method="restyle",
-                    args = list("visible", cols == col),
+                    args = list("visible", yvars == col),
                     label = col)
                 })
             )

R/linked_scatterplot.R

@@ -1,19 +1,26 @@
 #' linked_scatterplot
-#' 
+#'
 #' A scatterplot with links
-#' 
+#' @param x x values
+#' @param y y values
+#' @param groups Groups to color the points by.
+#' @param text Hovertext for the points
+#' @param title Plot title
+#' @param xlab,ylab X/Y axis title
+#' @param xlim,ylim Range of X/Y axis
+#' @param colors Colors to use for the groups
 #' @examples
 #' linked_scatterplot(
-#'  1:10, 
-#'  1:10, 
-#'  rep("https://www.google.com", 10), 
+#'  1:10,
+#'  1:10,
+#'  rep("https://www.google.com", 10),
 #'  groups=sample(letters[1:2], 10, replace=TRUE))
 #' @importFrom assertthat assert_that
 #' @export
-linked_scatterplot <- function(x, 
-        y, 
-        links, 
-        groups=rep("1", length(x)), 
+linked_scatterplot <- function(x,
+        y,
+        links,
+        groups=rep("1", length(x)),
         text = rep("", length(x)),
         title="",
         xlab="",
@@ -27,15 +34,15 @@ linked_scatterplot <- function(x,
         length(text) == length(y),
         length(colors) == length(unique(groups)))
 
-    createWidget("linked_scatterplot", 
-        x = list(x=x, 
+    createWidget("linked_scatterplot",
+        x = list(x=x,
             xlab=xlab,
             xlim=xlim,
-            y=y, 
+            y=y,
             ylab=ylab,
             ylim=ylim,
-            links=links, 
-            groups=groups, 
+            links=links,
+            groups=groups,
             colors=colors,
             title=title,
             text=text),

README.Rmd

@@ -14,7 +14,87 @@ output:
 plotlytalk
 ============
 
-This package contains a talk and related functions for an Edinbr meeting.
+This package contains a talk and related functions for an talk about [plotly](https://plot.ly/).
+
+Installation
+============
+```{r, eval=FALSE}
+devtools::install_github("alanocallaghan/plotlytalk")
+```
+```{r, echo=FALSE}
+suppressPackageStartupMessages(library(plotlytalk))
+suppressPackageStartupMessages(library(SummarizedExperiment))
+```
 
 Outline
--------
+=======
+
+The talk shows many examples of [ggplotly](https://www.rdocumentation.org/packages/plotly/versions/4.7.1/topics/ggplotly), some examples of how to plot using plotly, several functions which create custom plotly plots, and
+a custom htmlwidget written using JavaScript.
+
+The custom plots are shown below:
+
+## A boxplot with jittered points
+```{r}
+plotly_boxplot(iris[, -5])
+```
+
+## A line plot with selectable y variable
+```{r}
+set.seed(42)
+df <- lapply(1:26, function(x) rnorm(50)) %>% 
+    as.data.frame()
+colnames(df) <- letters
+df[["seq"]] <- 1:50
+
+df %>% dropdown_lineplot(x="seq", yvars = letters)
+```
+
+
+## A density plot of a matrix or data.frame
+```{r}
+
+plotly_density(
+    log2(assay(GBMdata[, 1:10]) + 0.5), 
+    palette=colorspace::rainbow_hcl,
+    xlab = "log<sub>2</sub>(reads + 0.5)") %>% 
+    layout(showlegend = FALSE)
+
+```
+
+## A scatter plot wherein clicking on a point opens a link in a new tab
+```{r}
+set.seed(42)
+tt <- GBMtopTable[sample(seq_len(nrow(GBMtopTable)), 1000), ]
+linked_scatterplot(
+    x = tt[["logFC"]],
+    xlab = "log<sub>2</sub>(fold-change)",
+    y = -log10(tt[["adj.P.Val"]]),
+    ylab = "-log<sub>10</sub>(FDR-adjusted p-value)",
+    xlim = c(-max(abs(tt[["logFC"]])), max(abs(tt[["logFC"]]))) * 1.1,
+    text = tt[["Text"]],
+    links = tt[["Links"]],
+    groups = tt[["Group"]],
+    title = "Glioblastoma - IDH1 mutant vs wt",
+    colors = c("#0000ff", "#000000", "#ff0000"))
+```
+
+
+
+Useful links
+============
+
+- [The site for this talk](https://alanocallaghan.github.io/plotlytalk/)
+- [github repository](https://github.com/Alanocallaghan/plotlytalk/)
+- [plotly (CRAN)](https://cran.r-project.org/web/packages/plotly/index.html)
+- [plotly for R (book)](https://plotly-book.cpsievert.me)
+- [plotly (R reference)](https://plot.ly/r/reference/)
+- [plotly (JavaScript reference)](https://plot.ly/javascript/reference/)
+- [plotly (github)](https://github.com/ropensci/plotly/)
+- [Carson Sievert's github (plotly R package maintainer)](https://github.com/cpsievert/)
+- [heatmaply (CRAN)](https://github.com/talgalili/heatmaply)
+- [heatmaply (github)](https://cran.r-project.org/web/packages/plotly/index.html)
+- [heatmaply (publication)](https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btx657/4562328)
+- [iheatmapr (CRAN)](https://cran.r-project.org/web/packages/iheatmapr/index.html)
+- [iheatmapr (github)](https://github.com/ropensci/iheatmapr)
+

codecov.yml

@@ -0,0 +1 @@
+comment: false

tests/testthat.R

@@ -0,0 +1,4 @@
+library(testthat)
+library(plotlytalk)
+
+test_check("plotlytalk")

tests/testthat/test_plotlytalk.R

@@ -0,0 +1,43 @@
+context("plotlytalk")
+
+
+test_that("boxplot works", {
+    expect_is(plotly_boxplot(iris[, -5]), "plotly")
+})
+test_that("density plot works", {
+    expect_is(
+        plotly_density(
+            log2(GBMdata@assays[[1]][, 1:10]) + 0.5),
+            palette=colorspace::rainbow_hcl,
+            xlab = "log<sub>2</sub>(reads + 0.5)") %>%
+            layout(showlegend = FALSE),
+        "plotly")
+})
+
+test_that("dropdown lineplot works", {
+    set.seed(42)
+    df <- lapply(1:26, function(x) rnorm(50)) %>%
+        as.data.frame()
+    colnames(df) <- letters
+    df[["seq"]] <- 1:50
+
+    p <- df %>% dropdown_lineplot(x="seq")
+    expect_is(p, "plotly")
+})
+
+test_that("linked scatterplot works", {
+    set.seed(42)
+    tt <- GBMtopTable[sample(seq_len(nrow(GBMtopTable)), 1000), ]
+    p <- linked_scatterplot(
+        x = tt[["logFC"]],
+        xlab = "log<sub>2</sub>(fold-change)",
+        y = -log10(tt[["adj.P.Val"]]),
+        ylab = "-log<sub>10</sub>(FDR-adjusted p-value)",
+        xlim = c(-max(abs(tt[["logFC"]])), max(abs(tt[["logFC"]]))) * 1.1,
+        text = tt[["Text"]],
+        links = tt[["Links"]],
+        groups = tt[["Group"]],
+        title = "Glioblastoma - IDH1 mutant vs wt",
+        colors = c("#0000ff", "#000000", "#ff0000"))
+    expect_is(p, "htmlwidget")
+})

vignettes/5_line_plots.rmd

@@ -30,5 +30,5 @@ df %>% plot_ly(x = ~seq, y = ~b, type = "scatter", mode = "lines")
 
 
 ```{r}
-df %>% dropdown_lineplot(x="seq")
+df %>% dropdown_lineplot(x="seq", yvars = letters)
 ```