evanglass · evanglass · Jan 6, 2023 · Jan 9, 2023 · Jan 9, 2023 · Jan 9, 2023
diff --git a/.github/workflows/R-CMD-check.yaml b/.github/workflows/R-CMD-check.yaml
@@ -2,9 +2,9 @@
 # Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help
 on:
   push:
-    branches: [master, develop, github-actions-test]
+    branches: [master, develop]
   pull_request:
-    branches: [master, develop, github-actions-test]
+    branches: [master, develop]
 
 name: R-CMD-check
 
@@ -25,9 +25,9 @@ jobs:
         with:
           extra-packages: |
             any::rcmdcheck
-            any::XML
             github::pmartR/pmartRdata@master
           needs: check
+          pak-version: devel # See https://github.com/r-lib/actions/issues/559
 
       - uses: r-lib/actions/setup-pandoc@v2
 

diff --git a/.github/workflows/lint.yaml b/.github/workflows/lint.yaml
@@ -0,0 +1,39 @@
+# Workflow derived from https://github.com/r-lib/actions/tree/v2/examples
+# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help
+on:
+  push:
+    branches: [master, develop]
+  pull_request:
+    branches: [master, develop]
+
+name: lint
+
+jobs:
+  lint:
+    runs-on: ubuntu-latest
+    env:
+      GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+      R_KEEP_PKG_SOURCE: yes
+    steps:
+      - uses: actions/checkout@v2
+
+      - uses: r-lib/actions/setup-r@v2
+        with:
+          use-public-rspm: true
+
+      - uses: r-lib/actions/setup-r-dependencies@v2
+        with:
+          extra-packages: |
+            r-lib/lintr
+            github::pmartR/pmartRdata@master
+            local::.
+          needs: lint
+          pak-version: devel # See https://github.com/r-lib/actions/issues/559
+
+      - name: Lint
+        run: |
+          library(lintr)
+          lint_package(linter = linters_with_defaults(
+            # options go here
+          ))
+        shell: Rscript {0}
diff --git a/.github/workflows/pkgdown.yaml b/.github/workflows/pkgdown.yaml
@@ -38,6 +38,7 @@ jobs:
             local::.
             github::pmartR/pmartRdata@master
           needs: website
+          pak-version: devel # See https://github.com/r-lib/actions/issues/559
 
       - name: Build site
         run: pkgdown::build_site_github_pages(new_process = FALSE, install = FALSE)

diff --git a/DESCRIPTION b/DESCRIPTION
@@ -41,9 +41,10 @@ Imports:
 Suggests:
     knitr,
     rmarkdown,
+    survival,
     testthat,
-    survival
+    trelliscopejs
 Remotes:
-    hafen/trelliscopejs
+    github::hafen/trelliscopejs
 RoxygenNote: 7.2.3
 Encoding: UTF-8
diff --git a/R/as.multiData.R b/R/as.multiData.R
@@ -12,7 +12,7 @@
 #'  a series of left joins. Defaults to FALSE.
 #' @param auto_fmeta logical indicator for whether to attempt to automatically
 #'  construct f_meta from the objects' sample information. Defaults to FALSE.
-#' @param match_samples logical indicator. If auto_fmeta = T, whether to attempt
+#' @param match_samples logical indicator. If auto_fmeta = TRUE, whether to attempt
 #'  to match the names in the sample columns in f_data across all objects in an
 #'  attempt to align them in f_meta. Defaults to TRUE.
 #'
@@ -38,7 +38,7 @@
 #' # Combine metabolomics and protein object into multidata, both must be log2 
 #' # and normalized.
 #' mymetab <- edata_transform(omicsData = metab_object, data_scale = "log2")
-#' mymetab <- normalize_global(omicsData = mymetab, subset_fn = "all", norm_fn = "median", apply_norm = T)
+#' mymetab <- normalize_global(omicsData = mymetab, subset_fn = "all", norm_fn = "median", apply_norm = TRUE)
 #' 
 #' mypro <- pro_object
 #' 
@@ -62,7 +62,7 @@ as.multiData <-
   function(...,
            f_meta = NULL,
            sample_intersect = F,
-           match_samples = T,
+           match_samples = TRUE,
            keep_sample_info = F,
            auto_fmeta = F) {
   omicsData_objects <- list(...)

diff --git a/R/as.omicsData.R b/R/as.omicsData.R
@@ -1189,7 +1189,7 @@ as.seqData <- function (e_data, f_data, e_meta = NULL,
   # Analyses must have raw counts
 
   nums <- e_data[which(colnames(e_data) != edata_cname)]
-  notint <- any(apply(nums, 2, function(col) (sum(col%%1, na.rm = T) != 0)))
+  notint <- any(apply(nums, 2, function(col) (sum(col%%1, na.rm = TRUE) != 0)))
   if(notint){
     warning("Non-integers detected. Analyses supported by pmartR for RNA-seq data require raw counts.")
   }

diff --git a/R/as.trelliData.R b/R/as.trelliData.R
@@ -239,12 +239,12 @@ as.trelliData.edata <- function(e_data,
 #' # Generate an example e_meta file for lipid data 
 #' lipid_emeta <- data.frame("Lipid" = lipid_pos_edata$Lipid, 
 #'   "LipidFamily" = lipid_pos_edata$Lipid %>% as.character() %>% 
-#'     strsplit("(", fixed = T) %>% lapply(function(el) {el[1]}) %>% unlist())
+#'     strsplit("(", fixed = TRUE) %>% lapply(function(el) {el[1]}) %>% unlist())
 #' 
 #' # Transform the data
 #' omicsData <- edata_transform(omicsData = lipid_pos_object, data_scale = "log2")
 #' omicsData$e_meta$LipidFamily <- omicsData$e_meta$Lipid %>% as.character() %>% 
-#'     strsplit("(", fixed = T) %>% lapply(function(el) {el[1]}) %>% unlist()
+#'     strsplit("(", fixed = TRUE) %>% lapply(function(el) {el[1]}) %>% unlist()
 #' 
 #' # Group the data by condition
 #' omicsData <- group_designation(omicsData = omicsData, main_effects = c("Virus"))

diff --git a/R/bpquant.R b/R/bpquant.R
@@ -222,9 +222,9 @@ bpquant_mod <- function (protein_sig, pi_not, max_proteoforms) {
   }
 
   ## order signatures by count##
-  cnt.ord = counts[order(counts, decreasing=T)]
+  cnt.ord = counts[order(counts, decreasing=TRUE)]
   if(nrow(sigs) > 1){
-    sig.ord = as.data.frame(sigs[order(counts, decreasing=T),])
+    sig.ord = as.data.frame(sigs[order(counts, decreasing=TRUE),])
   }else{
     sig.ord = sigs
   }
@@ -289,7 +289,7 @@ bpquant_mod <- function (protein_sig, pi_not, max_proteoforms) {
     for(j in 1:(nu-1)){
       tmp.rws = mat[apply(mat,1,sum)==j,]
       ord.var = apply(tmp.rws,1,function(x) as.numeric(paste(x,collapse="")))
-      mat.list[[j+1]] = tmp.rws[order(ord.var, decreasing=T),]
+      mat.list[[j+1]] = tmp.rws[order(ord.var, decreasing=TRUE),]
     }
     p_configs = do.call(rbind,mat.list)
   }

diff --git a/R/dim_reduction.R b/R/dim_reduction.R
@@ -89,7 +89,7 @@ dim_reduction <- function (omicsData, k = 2){
   }
 
   ## check for near zero variance features and remove ##
-  minvars = which(apply(temp_data, 1, var, na.rm = T) < 0.000001)
+  minvars = which(apply(temp_data, 1, var, na.rm = TRUE) < 0.000001)
   if(length(minvars) > 0){
     temp_data = temp_data[-minvars, ]
   }

diff --git a/R/edata_summary.R b/R/edata_summary.R
@@ -79,18 +79,18 @@ edata_summary <- function (omicsData, by = 'sample', groupvar = NULL) {
                               function(x){if(all(is.na(x))){
                                 mean(x)
                               }else{
-                                mean(x, na.rm = T)
+                                mean(x, na.rm = TRUE)
                               }}))
     avg = cbind(names(edata[, -edata_cname_id]), avg)
     names(avg)<- c("sample", "mean")
     rownames(avg)<- NULL
 
-    sd = as.data.frame(apply(edata[,-edata_cname_id], 2, sd, na.rm = T))
+    sd = as.data.frame(apply(edata[,-edata_cname_id], 2, sd, na.rm = TRUE))
     sd = cbind(names(edata[,-edata_cname_id]), sd)
     names(sd)<- c("sample", "sd")
     rownames(sd)<- NULL
 
-    mds = as.data.frame(apply(edata[,-edata_cname_id], 2, median, na.rm = T))
+    mds = as.data.frame(apply(edata[,-edata_cname_id], 2, median, na.rm = TRUE))
     mds = cbind(names(edata[,-edata_cname_id]), mds)
     names(mds)<- c("sample", "median")
     rownames(mds)<- NULL
@@ -111,12 +111,12 @@ edata_summary <- function (omicsData, by = 'sample', groupvar = NULL) {
       rownames(pct_obs)<- NULL
     }
 
-    min = as.data.frame(apply(edata[,-edata_cname_id], 2, min, na.rm = T))
+    min = as.data.frame(apply(edata[,-edata_cname_id], 2, min, na.rm = TRUE))
     min = cbind(names(edata[,-edata_cname_id]), min)
     names(min)<- c("sample", "min")
     rownames(min)<- NULL
 
-    max = as.data.frame(apply(edata[,-edata_cname_id], 2, max, na.rm = T))
+    max = as.data.frame(apply(edata[,-edata_cname_id], 2, max, na.rm = TRUE))
     max = cbind(names(edata[,-edata_cname_id]), max)
     names(max)<- c("sample", "max")
     rownames(max)<- NULL
@@ -144,18 +144,18 @@ edata_summary <- function (omicsData, by = 'sample', groupvar = NULL) {
                     function(x){if(all(is.na(x))){
                       mean(x)
                     }else{
-                      mean(x, na.rm = T)
+                      mean(x, na.rm = TRUE)
                     }})
         avg = data.frame(molecule = edata[, edata_cname_id],
                          mean = avg,
                          stringsAsFactors = F)
         names(avg)[1]<- edata_cname
-        sd = apply(edata[, -edata_cname_id], 1, sd, na.rm = T)
+        sd = apply(edata[, -edata_cname_id], 1, sd, na.rm = TRUE)
         sd = data.frame(molecule = edata[, edata_cname_id],
                         sd = sd,
                         stringsAsFactors = F)
         names(sd)[1]<- edata_cname
-        mds = apply(edata[, -edata_cname_id], 1, median, na.rm = T)
+        mds = apply(edata[, -edata_cname_id], 1, median, na.rm = TRUE)
         mds = data.frame(molecule = edata[, edata_cname_id],
                          median = mds,
                          stringsAsFactors = F)
@@ -166,12 +166,12 @@ edata_summary <- function (omicsData, by = 'sample', groupvar = NULL) {
                              pct_obs = pct_obs,
                              stringsAsFactors = F)
         names(pct_obs)[1]<- edata_cname
-        min = apply(edata[, -edata_cname_id], 1, min, na.rm = T)
+        min = apply(edata[, -edata_cname_id], 1, min, na.rm = TRUE)
         min = data.frame(molecule = edata[, edata_cname_id],
                          min = min,
                          stringsAsFactors = F)
         names(min)[1]<- edata_cname
-        max = apply(edata[, -edata_cname_id], 1, max, na.rm = T)
+        max = apply(edata[, -edata_cname_id], 1, max, na.rm = TRUE)
         max = data.frame(molecule = edata[, edata_cname_id],
                          max = max,
                          stringsAsFactors = F)
@@ -226,14 +226,14 @@ edata_summary <- function (omicsData, by = 'sample', groupvar = NULL) {
                               function(x){if(all(is.na(x))){
                                 mean(x)
                               }else{
-                                mean(x, na.rm = T)
+                                mean(x, na.rm = TRUE)
                               }})
         names(avg)[which(colnames(avg)== ".")]<- "value"
         avg = reshape2::dcast(avg, formula = formula2)
-        std_dev = reshape2::dcast(edata_melt, formula = formula1, sd, na.rm = T)
+        std_dev = reshape2::dcast(edata_melt, formula = formula1, sd, na.rm = TRUE)
         names(std_dev)[which(colnames(std_dev)== ".")]<- "value"
         std_dev = reshape2::dcast(std_dev, formula = formula2)
-        mds = reshape2::dcast(edata_melt, formula = formula1, median, na.rm = T)
+        mds = reshape2::dcast(edata_melt, formula = formula1, median, na.rm = TRUE)
         names(mds)[which(colnames(mds)== ".")]<- "value"
         mds = reshape2::dcast(mds, formula = formula2)
         pct_obs = reshape2::dcast(edata_melt, formula = formula1,
@@ -244,15 +244,15 @@ edata_summary <- function (omicsData, by = 'sample', groupvar = NULL) {
                                function(x){if(all(is.na(x))){
                                  min(x)
                                }else{
-                                 min(x, na.rm = T)
+                                 min(x, na.rm = TRUE)
                                }})
         names(mins)[which(colnames(mins)== ".")]<- "value"
         mins = reshape2::dcast(mins, formula = formula2)
         maxs = reshape2::dcast(edata_melt, formula = formula1,
                                function(x){if(all(is.na(x))){
                                  max(x)
                                }else{
-                                 max(x, na.rm = T)
+                                 max(x, na.rm = TRUE)
                                }})
         names(maxs)[which(colnames(maxs)== ".")]<- "value"
         maxs = reshape2::dcast(maxs, formula = formula2)
@@ -309,14 +309,14 @@ edata_summary <- function (omicsData, by = 'sample', groupvar = NULL) {
                             function(x){if(all(is.na(x))){
                               mean(x)
                             }else{
-                              mean(x, na.rm = T)
+                              mean(x, na.rm = TRUE)
                             }})
       names(avg)[which(colnames(avg)== ".")]<- "value"
       avg = reshape2::dcast(avg, formula = formula2)
-      std_dev = reshape2::dcast(edata_melt, formula = formula1, sd, na.rm = T)
+      std_dev = reshape2::dcast(edata_melt, formula = formula1, sd, na.rm = TRUE)
       names(std_dev)[which(colnames(std_dev)== ".")]<- "value"
       std_dev = reshape2::dcast(std_dev, formula = formula2)
-      mds = reshape2::dcast(edata_melt, formula = formula1, median, na.rm = T)
+      mds = reshape2::dcast(edata_melt, formula = formula1, median, na.rm = TRUE)
       names(mds)[which(colnames(mds)== ".")]<- "value"
       mds = reshape2::dcast(mds, formula = formula2)
       pct_obs = reshape2::dcast(edata_melt, formula = formula1,
@@ -327,15 +327,15 @@ edata_summary <- function (omicsData, by = 'sample', groupvar = NULL) {
                              function(x){if(all(is.na(x))){
                                min(x)
                              }else{
-                               min(x, na.rm = T)
+                               min(x, na.rm = TRUE)
                              }})
       names(mins)[which(colnames(mins)== ".")]<- "value"
       mins = reshape2::dcast(mins, formula = formula2)
       maxs = reshape2::dcast(edata_melt, formula = formula1,
                              function(x){if(all(is.na(x))){
                                max(x)
                              }else{
-                               max(x, na.rm = T)
+                               max(x, na.rm = TRUE)
                              }})
       names(maxs)[which(colnames(maxs)== ".")]<- "value"
       maxs = reshape2::dcast(maxs, formula = formula2)
@@ -407,14 +407,14 @@ edata_summary <- function (omicsData, by = 'sample', groupvar = NULL) {
                             function(x){if(all(is.na(x))){
                               mean(x)
                             }else{
-                              mean(x, na.rm = T)
+                              mean(x, na.rm = TRUE)
                             }})
       names(avg)[which(colnames(avg)== ".")]<- "value"
       avg = reshape2::dcast(avg, formula = formula2)
-      std_dev = reshape2::dcast(edata_melt, formula = formula1, sd, na.rm = T)
+      std_dev = reshape2::dcast(edata_melt, formula = formula1, sd, na.rm = TRUE)
       names(std_dev)[which(colnames(std_dev)== ".")]<- "value"
       std_dev = reshape2::dcast(std_dev, formula = formula2)
-      mds = reshape2::dcast(edata_melt, formula = formula1, median, na.rm = T)
+      mds = reshape2::dcast(edata_melt, formula = formula1, median, na.rm = TRUE)
       names(mds)[which(colnames(mds)== ".")]<- "value"
       mds = reshape2::dcast(mds, formula = formula2)
       pct_obs = reshape2::dcast(edata_melt, formula = formula1,
@@ -425,15 +425,15 @@ edata_summary <- function (omicsData, by = 'sample', groupvar = NULL) {
                              function(x){if(all(is.na(x))){
                                min(x)
                              }else{
-                               min(x, na.rm = T)
+                               min(x, na.rm = TRUE)
                              }})
       names(mins)[which(colnames(mins)== ".")]<- "value"
       mins = reshape2::dcast(mins, formula = formula2)
       maxs = reshape2::dcast(edata_melt, formula = formula1,
                              function(x){if(all(is.na(x))){
                                max(x)
                              }else{
-                               max(x, na.rm = T)
+                               max(x, na.rm = TRUE)
                              }})
       names(maxs)[which(colnames(maxs)== ".")]<- "value"
       maxs = reshape2::dcast(maxs, formula = formula2)