Update 51 packages

episodes/01-introduction-to-high-dimensional-data.Rmd

@@ -373,7 +373,8 @@ These data include information collected from the
 assay as well as associated metadata from individuals from whom samples were
 taken.
 
-```{r libsload}
+```{r libsload, message=FALSE}
+library("SummarizedExperiment")
 methylation <- readRDS("data/methylation.rds")
 head(colData(methylation))
 

episodes/02-high-dimensional-regression.Rmd

@@ -115,14 +115,17 @@ order <- order(age)
 age_ord <- age[order]
 methyl_mat_ord <- methyl_mat[, order]
 
+## create annotation df with rownames matching columns of methylation matrix
+ann_df <- data.frame(age = age_ord, row.names=colnames(methyl_mat_ord))
+
 # plot heatmap
 pheatmap(methyl_mat_ord, 
          cluster_cols = FALSE, 
          show_rownames = FALSE, 
          show_colnames = FALSE, 
          legend_title = "M-value", 
          main = "Feature vs Sample", 
-         annotation_col = data.frame(age = age_ord))
+         annotation_col = ann_df)
 ```
 
 :::::::::::::::::::::::::::::::::::::::  challenge

episodes/03-regression-regularisation.Rmd

@@ -337,7 +337,7 @@ data into training and test sets, fit a linear model and calculate the errors. F
 calculate the training error. Let's start by splitting the data into training and test sets:
 
 ```{r data}
-methylation <- readRDS("/data/methylation.rds")
+methylation <- readRDS("data/methylation.rds")
 
 library("SummarizedExperiment")
 age <- methylation$Age
@@ -921,13 +921,13 @@ plot_elastic(0.75)
   but the paths are a bit less
   extreme than with pure LASSO; similar to ridge.
   ```{r elastic, fig.cap="Line plot showing coefficient values from an elastic net model against L1 norm.", fig.alt="A line plot showing coefficient values from an elastic net model against L1 norm. The coefficients, generally, suddenly become zero as L1 norm decreases. However, some coefficients increase in size before decreasing as L1 norm decreases."}
-  elastic <- glmnet(methyl_mat[, -1], age, alpha = 0.5)
+  elastic <- glmnet(methyl_mat, age, alpha = 0.5)
   plot(elastic)
   ```
 2. The process of model selection is similar for elastic net models as for
   LASSO models.
   ```{r elastic-cv, fig.cap="A plot of the cross-validation mean squared error of an elastic net model against log lambda."}
-  elastic_cv <- cv.glmnet(methyl_mat[, -1], age, alpha = 0.5)
+  elastic_cv <- cv.glmnet(methyl_mat, age, alpha = 0.5)
   plot(elastic_cv)
   ```
 3. You can see that the coefficients from these two methods are broadly

episodes/07-hierarchical.Rmd

@@ -98,7 +98,8 @@ clustering is really useful, and then we can understand how to apply it in more
 detail. To do this, we'll return to the large [`methylation`](https://carpentries-incubator.github.io/high-dimensional-stats-r/data/index.html) dataset we worked
 with in the regression lessons. Let's load and visually inspect the data:
 
-```{r}
+```{r, message=FALSE}
+library("SummarizedExperiment")
 methyl <- readRDS("data/methylation.rds")
 
 # transpose this Bioconductor dataset to show features in columns
@@ -110,6 +111,7 @@ appear to have a similar methylation levels across all rows. However, they are
 all quite jumbled at the moment, so it's hard to tell how many line up exactly.
 
 ```{r heatmap-noclust, echo=FALSE, fig.cap="Heatmap of methylation data.", fig.alt="Heatmap of methylation level with individuals along the y axis and methylation sites along the x axis. Red colours indicate high methylation levels (up to around 4), blue colours indicate low methylation levels (to around -4) and white indicates methylation levels close to zero. There are many vertical blue and red stripes."}
+library("pheatmap")
 pheatmap(methyl_mat,
          legend_title = "Methylation level",
          cluster_rows = FALSE, 
@@ -133,6 +135,7 @@ groups features based on dissimilarity (here, Euclidean distance) and orders
 rows and columns to show clustering of features and observations.
 
 ```{r heatmap-clust, fig.cap="Heatmap of methylation data clustered by methylation sites and individuals.", fig.alt="Heatmap of methylation level with individuals along the y axis and methylation sites along the x axis, clustered by methylation sites and individuals. Red colours indicate high methylation levels (up to around 4), blue colours indicate low methylation levels (to around -4) and white indicates methylation levels close to zero. This time, the individuals and methylation sites are clustered and the plot fades from vertical red lines on the left side to vertical blue lines on the right side. There are two, arguably three, white stripes towards the middle of the plot."}
+library("pheatmap")
 pheatmap(methyl_mat,
          legend_title = "Methylation level",
          cluster_rows = TRUE, 

renv/activate.R

@@ -2,7 +2,8 @@
 local({
 
   # the requested version of renv
-  version <- "1.1.5"
+  version <- "1.1.7"
+  attr(version, "md5") <- "dd5d60f155dadff4c88c2fc6680504b4"
   attr(version, "sha") <- NULL
 
   # the project directory
@@ -168,6 +169,16 @@ local({
     if (quiet)
       return(invisible())
 
+    # also check for config environment variables that should suppress messages
+    # https://github.com/rstudio/renv/issues/2214
+    enabled <- Sys.getenv("RENV_CONFIG_STARTUP_QUIET", unset = NA)
+    if (!is.na(enabled) && tolower(enabled) %in% c("true", "1"))
+      return(invisible())
+
+    enabled <- Sys.getenv("RENV_CONFIG_SYNCHRONIZED_CHECK", unset = NA)
+    if (!is.na(enabled) && tolower(enabled) %in% c("false", "0"))
+      return(invisible())
+
     msg <- sprintf(fmt, ...)
     cat(msg, file = stdout(), sep = if (appendLF) "\n" else "")
 
@@ -215,6 +226,16 @@ local({
     section <- header(sprintf("Bootstrapping renv %s", friendly))
     catf(section)
 
+    # try to install renv from cache
+    md5 <- attr(version, "md5", exact = TRUE)
+    if (length(md5)) {
+      pkgpath <- renv_bootstrap_find(version)
+      if (length(pkgpath) && file.exists(pkgpath)) {
+        file.copy(pkgpath, library, recursive = TRUE)
+        return(invisible())
+      }
+    }
+
     # attempt to download renv
     catf("- Downloading renv ... ", appendLF = FALSE)
     withCallingHandlers(
@@ -240,7 +261,6 @@ local({
 
     # add empty line to break up bootstrapping from normal output
     catf("")
-
     return(invisible())
   }
 
@@ -256,14 +276,22 @@ local({
     # check for repos override
     repos <- Sys.getenv("RENV_CONFIG_REPOS_OVERRIDE", unset = NA)
     if (!is.na(repos)) {
-
-      # check for RSPM; if set, use a fallback repository for renv
-      rspm <- Sys.getenv("RSPM", unset = NA)
-      if (identical(rspm, repos))
-        repos <- c(RSPM = rspm, CRAN = cran)
-
-      return(repos)
-
+
+      # split on ';' if present
+      parts <- strsplit(repos, ";", fixed = TRUE)[[1L]]
+
+      # split into named repositories if present
+      idx <- regexpr("=", parts, fixed = TRUE)
+      keys <- substring(parts, 1L, idx - 1L)
+      vals <- substring(parts, idx + 1L)
+      names(vals) <- keys
+
+      # if we have a single unnamed repository, call it CRAN
+      if (length(vals) == 1L && identical(keys, ""))
+        names(vals) <- "CRAN"
+
+      return(vals)
+
     }
 
     # check for lockfile repositories
@@ -511,6 +539,51 @@ local({
 
   }
 
+  renv_bootstrap_find <- function(version) {
+
+    path <- renv_bootstrap_find_cache(version)
+    if (length(path) && file.exists(path)) {
+      catf("- Using renv %s from global package cache", version)
+      return(path)
+    }
+
+  }
+
+  renv_bootstrap_find_cache <- function(version) {
+
+    md5 <- attr(version, "md5", exact = TRUE)
+    if (is.null(md5))
+      return()
+
+    # infer path to renv cache
+    cache <- Sys.getenv("RENV_PATHS_CACHE", unset = "")
+    if (!nzchar(cache)) {
+      root <- Sys.getenv("RENV_PATHS_ROOT", unset = NA)
+      if (!is.na(root))
+        cache <- file.path(root, "cache")
+    }
+
+    if (!nzchar(cache)) {
+      tools <- asNamespace("tools")
+      if (is.function(tools$R_user_dir)) {
+        root <- tools$R_user_dir("renv", "cache")
+        cache <- file.path(root, "cache")
+      }
+    }
+
+    # start completing path to cache
+    file.path(
+      cache,
+      renv_bootstrap_cache_version(),
+      renv_bootstrap_platform_prefix(),
+      "renv",
+      version,
+      md5,
+      "renv"
+    )
+
+  }
+
   renv_bootstrap_download_tarball <- function(version) {
 
     # if the user has provided the path to a tarball via
@@ -979,7 +1052,7 @@ local({
 
   renv_bootstrap_validate_version_release <- function(version, description) {
     expected <- description[["Version"]]
-    is.character(expected) && identical(expected, version)
+    is.character(expected) && identical(c(expected), c(version))
   }
 
   renv_bootstrap_hash_text <- function(text) {
@@ -1181,6 +1254,18 @@ local({
 
   }
 
+  renv_bootstrap_cache_version <- function() {
+    # NOTE: users should normally not override the cache version;
+    # this is provided just to make testing easier
+    Sys.getenv("RENV_CACHE_VERSION", unset = "v5")
+  }
+
+  renv_bootstrap_cache_version_previous <- function() {
+    version <- renv_bootstrap_cache_version()
+    number <- as.integer(substring(version, 2L))
+    paste("v", number - 1L, sep = "")
+  }
+
   renv_json_read <- function(file = NULL, text = NULL) {
 
     jlerr <- NULL