Merge pull request #56 from singha53/alexa

bug: fix alexa functionality
singha53-zz · May 5, 2020 · 3dbff55 · 3dbff55
2 parents 3991653 + dc14cab
commit 3dbff55
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Showing 3 changed files with 35 additions and 22 deletions.
diff --git a/R/alexa_functions.R b/R/alexa_functions.R
@@ -1,8 +1,10 @@
 #' @export
 #' @rdname alexaMetadata
-alexa_metadata <- function(demo, group, trim, format) {
+alexa_metadata <- function(demo, group, trim, format, user_id, s3_bucket) {
   result <- omicsBioAnalytics::computeDescriptiveStats(demo,
     group, trim, format)
+  print("result")
+  print(result)
   # save figures to tempdir()
   mapply(function(var, var_type) {
     if(var_type == "continuous") {
@@ -14,15 +16,15 @@ alexa_metadata <- function(demo, group, trim, format) {
         xlab(paste0(group, "\n ", paste(paste0(levels(demo[, group]), " (n=", table(demo[, group]), ") "), collapse = ', '))) +
         theme(legend.position = "none") +
         theme_bw()
-      ggsave(paste0(tempdir(), "/", paste(userID, "ds", var, sep="-"), ".png"), metadataPlot, device = "png", width = 4, height = 4)
-      put_object(paste0(tempdir(), "/", paste(userID, "ds", var, sep="-"), ".png"), bucket = S3Bucket)
+      ggsave(paste0(tempdir(), "/", paste(user_id, "ds", var, sep="-"), ".png"), metadataPlot, device = "png", width = 4, height = 4)
+      put_object(paste0(tempdir(), "/", paste(user_id, "ds", var, sep="-"), ".png"), bucket = s3_bucket)
     } else if (var_type == "categorical") {
       df <- table(demo[, var], demo[, group])
       tg = gridExtra::tableGrob(df)
       h = grid::convertHeight(sum(tg$heights), "in", TRUE)
       w = grid::convertWidth(sum(tg$widths), "in", TRUE)
-      ggplot2::ggsave(paste0(tempdir(), "/", paste(userID, "ds", var, sep="-"), ".png"), tg, width=w, height=h)
-      put_object(paste0(tempdir(), "/", paste(userID, "ds", var, sep="-"), ".png"), bucket = S3Bucket)
+      ggplot2::ggsave(paste0(tempdir(), "/", paste(user_id, "ds", var, sep="-"), ".png"), tg, width=w, height=h)
+      put_object(paste0(tempdir(), "/", paste(user_id, "ds", var, sep="-"), ".png"), bucket = s3_bucket)
     } else {
       NA
     }
@@ -32,7 +34,7 @@ alexa_metadata <- function(demo, group, trim, format) {
 
 #' @export
 #' @rdname alexaEda
-alexaEda = function(demo, group, omicsData){
+alexaEda = function(demo, group, omicsData, user_id, s3_bucket){
   result <- lapply(names(omicsData), function(i){
     pcs = prcomp(
       omicsData[[i]],
@@ -51,8 +53,8 @@ alexaEda = function(demo, group, omicsData){
         xSize = 15, ySize = 15, xAxisSize = 15, yAxisSize = 15) +
       ylab(paste0("PC2 (", 100*signif(summary(pcs)$importance["Proportion of Variance", "PC2"], 2), "%)")) +
       xlab(paste0("PC1 (", 100*signif(summary(pcs)$importance["Proportion of Variance", "PC1"], 2), "%)"))
-    ggsave(paste0(tempdir(), "/", paste(userID, "eda", i, sep="-"), ".png"), pcaPlot, device = "png", width = 4, height = 4)
-    put_object(paste0(tempdir(), "/", paste(userID, "eda", i, sep="-"), ".png"), bucket = S3Bucket)
+    ggsave(paste0(tempdir(), "/", paste(user_id, "eda", i, sep="-"), ".png"), pcaPlot, device = "png", width = 4, height = 4)
+    put_object(paste0(tempdir(), "/", paste(user_id, "eda", i, sep="-"), ".png"), bucket = s3_bucket)
 
     list(primary = i,
       secondary = paste0("The first two PCS explain ", 100*signif(summary(pcs)$importance["Cumulative Proportion", "PC2"], 2), "% of the variation in the ", i, " dataset."),
@@ -66,7 +68,7 @@ alexaEda = function(demo, group, omicsData){
 
 #' @export
 #' @rdname alexaDexp
-alexaDexp = function(demo, group, omicsData){
+alexaDexp = function(demo, group, omicsData, user_id, s3_bucket){
   diffexp = function(datasets, response){
     design <- model.matrix(~response)
     lapply(datasets, function(i){
@@ -94,10 +96,10 @@ alexaDexp = function(demo, group, omicsData){
         xlab(expression("log2 fold-change")) +
         ggrepel::geom_text_repel(data = filter(top, adj.P.Val < fdr), aes(label = FeatureName))
 
-      ggsave(paste0(tempdir(), "/", paste(userID, "dexp", name, fdr, sep="-"), ".png"), volcanoPlot, device = "png", width = 4, height = 3.7)
-      put_object(paste0(tempdir(), "/", paste(userID, "dexp", name, fdr, sep="-"), ".png"), bucket = S3Bucket)
+      ggsave(paste0(tempdir(), "/", paste(user_id, "dexp", name, fdr, sep="-"), ".png"), volcanoPlot, device = "png", width = 4, height = 3.7)
+      put_object(paste0(tempdir(), "/", paste(user_id, "dexp", name, fdr, sep="-"), ".png"), bucket = s3_bucket)
 
-      # ggsave(paste0(tempdir(), "/", paste(userID, name, fdr, sep="-"), ".png"), volcanoPlot, device = "png")
+      # ggsave(paste0(tempdir(), "/", paste(user_id, name, fdr, sep="-"), ".png"), volcanoPlot, device = "png")
       up <- sum(top$logFC > 0 & top$adj.P.Val < fdr)
       down <- sum(top$logFC < 0 & top$adj.P.Val < fdr)
       list(primary = name,

diff --git a/R/metadata_helperFunctions.R b/R/metadata_helperFunctions.R
@@ -174,12 +174,13 @@ summariseContVar = function(demo, group, format){
 }
 #
 # library(omicsBioAnalytics)
-# data("covid19")
-# demo <- covid19$demo
-# group  <-  "group"
+# data("heartFailure")
+# demo <- heartFailure$demo
+# group  <-  "hospitalizations"
 # trim  <-  0.5
 # format = "apl"
 # result <- computeDescriptiveStats(demo, group, trim, format)
+# result
 # library(gridExtra)
 # library(grid)
 #
@@ -224,13 +225,13 @@ computeDescriptiveStats = function(demo, group = NULL, trim = 0.5, format){
       NA
     }
   } else {
-    if (is.data.frame(cont) & is.data.frame(cat)){
+    if (is.list(cont) & is.list(cat)){
       list(apl = append(cont, cat),
         var_type = c(rep("continuous", length(cont)), rep("categorical", length(cat))))
-    } else if (is.data.frame(cont) & !is.data.frame(cat)) {
+    } else if (is.list(cont) & !is.list(cat)) {
       list(apl = cont,
         var_type = rep("continuous", length(cont)))
-    } else if (!is.data.frame(cont) & is.data.frame(cat)) {
+    } else if (!is.list(cont) & is.list(cat)) {
       list(apl = cat,
         var_type = rep("categorical", length(cat)))
     } else {

diff --git a/inst/app/server.R b/inst/app/server.R
@@ -169,17 +169,27 @@ function(input, output, session) {
           responseColumnName <- isolate({data_upload_ui_vars$response_var()})
           responseRefLevel <- isolate({data_upload_ui_vars$ref_var()})
           response <- isolate({relevel(factor(as.character(demo[, responseColumnName])), ref = responseRefLevel)})
-          omicsData <- isolate({getOmicsData()})
+          omicsData <- isolate({data_upload_server_vars$get_omics_data()})
 
           dynamodbAttr <- list()
           # analyze demo data and save images to S3
-          dynamodbAttr$ds <- omicsBioAnalytics::alexa_metadata(demo, group = responseColumnName, trim = 0.5, format = "APL")
+          dynamodbAttr$ds <- omicsBioAnalytics::alexa_metadata(demo,
+            group = responseColumnName,
+            trim = 0.5,
+            format = "APL",
+            user_id, s3_bucket)
 
           # EDA and save images to S3
-          dynamodbAttr$eda <- omicsBioAnalytics::alexaEda(demo, group = responseColumnName, omicsData)
+          dynamodbAttr$eda <- omicsBioAnalytics::alexaEda(demo,
+            group = responseColumnName,
+            omicsData,
+            user_id, s3_bucket)
 
           # Perform Differential Expression Analysis and save images to S3
-          dynamodbAttr$dexp <- omicsBioAnalytics::alexaDexp(demo, group = responseColumnName, omicsData)
+          dynamodbAttr$dexp <- omicsBioAnalytics::alexaDexp(demo,
+            group = responseColumnName,
+            omicsData,
+            user_id, s3_bucket)
 
           # save dynamodb attributes to dynamodb_table_name (set in global.R) for user_id (set in global.R)
           omicsBioAnalytics::put_item(dynamodb_table_name, list(id = user_id, phoneNumber = jsonlite::toJSON(dynamodbAttr)))