Merge pull request #5 from danforthcenter/vignette

update to use aws

R/asvDist.R

@@ -112,9 +112,11 @@ asvDist <- function(asvTab, asvCols = NULL, method = "spearman",
   #* *plotting*
   if (plot) {
     # consider grouping things here maybe with hclust.
-    p <- ggplot2::ggplot(ldf, ggplot2::aes(x = .data[["c1"]],
-                                           y = .data[["c2"]],
-                                           fill = ldf[[method]])) +
+    p <- ggplot2::ggplot(ldf, ggplot2::aes(
+      x = .data[["c1"]],
+      y = .data[["c2"]],
+      fill = ldf[[method]]
+    )) +
       ggplot2::geom_tile(color = NA, linewidth = 0) +
       viridis::scale_fill_viridis(na.value = "grey100") +
       ggplot2::labs(fill = method) +

R/netcomi2scb.R

@@ -27,10 +27,10 @@
 #' @examples
 #' \dontrun{
 #' if ("NetCoMi" %in% installed.packages()) {
-#' microNetObj <- NetCoMi::netConstruct(as.matrix(asv[, grepl("ASV", colnames(asv))]),
-#'   measure = "spearman", sparsMethod = "t-test", alpha = 0.7
-#' )
-#' net <- netcomi2scb(microNetObj)
+#'   microNetObj <- NetCoMi::netConstruct(as.matrix(asv[, grepl("ASV", colnames(asv))]),
+#'     measure = "spearman", sparsMethod = "t-test", alpha = 0.7
+#'   )
+#'   net <- netcomi2scb(microNetObj)
 #' }
 #' }
 #' @export

R/qc.R

@@ -83,8 +83,10 @@ qc <- function(file = NULL, asvTab = NULL, taxa = NULL, asvAbnd = 100, sampleAbn
   asvTab <- taxa_filtering_output$asvTab
   taxa <- taxa_filtering_output$taxa
   #* `Sample Abundance filtering`
-  sample_filtering_output <- .qc_sample_abundance_filter(asvTab, sampleAbnd, metadata, return_removed,
-                                                         separate, split)
+  sample_filtering_output <- .qc_sample_abundance_filter(
+    asvTab, sampleAbnd, metadata, return_removed,
+    separate, split
+  )
   asvTab <- sample_filtering_output$asvTab
   metadata <- sample_filtering_output$metadata
   removed <- sample_filtering_output$removed

R/threshPlot.R

@@ -38,8 +38,10 @@ threshPlot <- function(thresh, asv, asvCols = NULL, phenotype = NULL, unit = "as
     clusters <- unique(nodes[[clusterCol]])
     clust_ag <- do.call(cbind, lapply(clusters, function(clust) {
       asvs_in_cluster <- nodes[nodes[[clusterCol]] == clust, "asv"]
-      setNames(data.frame(rowSums(as.data.frame(asv[, c(asvs_in_cluster)]))),
-               c(paste0("cluster_", clust)))
+      setNames(
+        data.frame(rowSums(as.data.frame(asv[, c(asvs_in_cluster)]))),
+        c(paste0("cluster_", clust))
+      )
     }))
     asv <- cbind(asv[, -which(grepl("ASV", colnames(asv)))], clust_ag)
   }

R/threshUpset.R

@@ -54,8 +54,9 @@ threshUpset <- function(thresh, mode = "phenotype",
   sub_upset_data[[pvalcol]] <- ifelse(sub_upset_data[[pvalcol]] < cutoff, TRUE, FALSE)
   data.table::setDT(sub_upset_data)
   upsetPlotData <- as.data.frame(data.table::dcast(sub_upset_data,
-                                                   asv ~ phenotype,
-                                                   value.var = pvalcol))
+    asv ~ phenotype,
+    value.var = pvalcol
+  ))
   p <- ComplexUpset::upset(upsetPlotData, intersect = colnames(upsetPlotData)[-1])
   p[[2]] <- p[[2]] +
     ggplot2::labs(

tools/linting.R

@@ -18,7 +18,7 @@ style_pkg("~/syncomBuildR", dry = "off", scope = "line_breaks")
 style_pkg("~/syncomBuildR", dry = "off", scope = "tokens")
 
 if(FALSE){
-  file = "~/syncomBuildR/R/netThresh.R"
+  file = "~/syncomBuildR/vignettes/dada2.Rmd"
   styler::style_file(file, scope = "line_breaks")
   lintr::lint(file, linters = lintr::linters_with_defaults(lintr::line_length_linter(length = 105L),
                                                            lintr::object_name_linter(styles = c("snake_case", "symbols",