Version 1.1.3

- Occasionally, eBayes(trend=TRUE) fails for intensity-based data, particularly when the distribution of quantified features is not uniform across samples. In these cases, eBayes(trend=FALSE) is run instead, and a warning message is printed. We highly encourage users who encounter this warning to carefully examine their data, and re-perform statistical analysis as needed. Typically, setting a stricter missing value filter will fix the issue.
- The one-sample T-test is now fixed. It was not working due to an error in passing a parameter to the function.
- An issue with heatmap color annotations was fixed. The issue occured during conversion of certain annotation group names to R-compliant names.

global.R

@@ -32,7 +32,7 @@ options(repos = BiocManager::repositories())
 ## set to FALSE if deployed to RStudio Connect 
 PACMAN <- FALSE
 ## version number
-VER <- "1.1.2"
+VER <- "1.1.3"
 ## maximal file size for upload
 MAXSIZEMB <<- 1024
 ## list of strings indicating missing data

server.R

@@ -1377,8 +1377,9 @@ shinyServer(
           }
 
           ## robustify levels of group variable
-          #cdesc[, input$grp.gct3] <- make.names(cdesc[, input$grp.gct3])
-          #cdesc[, input$grp.norm] <- make.names(cdesc[, input$grp.norm])
+          ## prevent NA from being converted (TEXT FILE INPUT ONLY)
+          cdesc[!is.na(cdesc[,input$grp.gct3]), input$grp.gct3] <- make.names(cdesc[!is.na(cdesc[,input$grp.gct3]), input$grp.gct3])
+          cdesc[!is.na(cdesc[,input$grp.norm]), input$grp.norm] <- make.names(cdesc[!is.na(cdesc[,input$grp.norm]), input$grp.norm])
           global.input$cdesc <- cdesc
 
           # initialize grp file

src/helptext.R

@@ -32,6 +32,12 @@ printHTML <- function(input, output, session, what, error=NULL, global.input=NUL
     if(what == 'cl'){
       txt <- '<h4><font color="red">What\'s new?</font></h4>
 <font size=\"3\">
+<b>v1.1.3 February 8, 2023</b>\
+<ul>
+<li>Occasionally, eBayes(trend=TRUE) fails for intensity-based data, particularly when the distribution of quantified features is not uniform across samples. In these cases, eBayes(trend=FALSE) is run instead, and a warning message is printed. We highly encourage users who encounter this warning to carefully examine their data, and re-perform statistical analysis as needed. Typically, setting a stricter missing value filter will fix the issue.
+<li> The one-sample T-test is now fixed. It was not working due to an error in passing a parameter to the function.
+<li> An issue with heatmap color annotations was fixed. The issue occured during conversion of certain annotation group names to R-compliant names.
+</ul>
 <b>v1.1.2 January 18, 2023</b>\
 <ul>
 <li>Previously, raw log-fold changes were median-centered by default. Raw log-fold changes are no longer median-centered so that they accurately reflect the fold change before any normalization is performed.

src/modT.R

@@ -109,7 +109,7 @@ modT.test <- function (d, output.prefix, id.col=NULL, data.col=NULL, fix.id=FALS
 
     ## moderated t test
       ##View(data)
-    mod.t.result <- moderated.t (data, intensity)
+    mod.t.result <- moderated.t (data, intensity=intensity)
     ##View(data)
   if (use.adj.pvalue) mod.sig <- mod.t.result [,'adj.P.Val'] <= p.value.alpha
   else  mod.sig <- mod.t.result [,'P.Value'] <= p.value.alpha
@@ -186,8 +186,14 @@ modF.test <- function (d, class.vector, output.prefix, id.col=NULL,
   data.rownorm <- sweep (data, MARGIN=1, STATS=apply (data, 1, mean, na.rm=TRUE))
   fit <- lmFit (data.rownorm, design)
   #trend=TRUE for intensity data
+  #if it fails, do trend=FALSE
   if(intensity){
-    fit <- eBayes (fit, trend=TRUE, robust=TRUE)
+    fit <- tryCatch({
+      eBayes (fit, trend=TRUE, robust=TRUE)},
+      error= function(e){
+        shinyalert("Setting intensity-trend failed. Performing with trend=FALSE. This usually occurs when the distribution of detected features is not uniform across samples. Please evaluate your data and consider re-running analysis with a stricter missing value filter.",type="warning",immediate=T)
+        eBayes (fit, trend=FALSE, robust=TRUE)
+      })
   }else{
     fit <- eBayes (fit, robust=TRUE)
   }
@@ -248,9 +254,15 @@ moderated.t <- function (data, design=NULL, intensity=FALSE) {
     ## two sample test
     if(!is.null(design)){
         m <- lmFit (data.matrix, design)
-        #trend=TRUE for intensity data
+        #try trend=TRUE for intensity data
+        #if it fails, perform trend=FALSE
         if(intensity){
-          m <- eBayes (m, trend=TRUE, robust=TRUE)
+          m <- tryCatch({
+            eBayes (m, trend=TRUE, robust=TRUE)},
+            error= function(e){
+              shinyalert("Setting intensity-trend failed. Performing with trend=FALSE. This usually occurs when the distribution of detected features is not uniform across samples. Please evaluate your data and consider re-running analysis with a stricter missing value filter.",type="warning",immediate=T)
+              eBayes (m, trend=FALSE, robust=TRUE)
+            })
         }else{
           m <- eBayes (m, robust=TRUE)
         }
@@ -261,12 +273,8 @@ moderated.t <- function (data, design=NULL, intensity=FALSE) {
         ##cat('here2 ')
         m <- lmFit (data.matrix, method='robust')
         ##cat('here3 ')
-        #trend=TRUE for intensity data
-        if(intensity){
-          m <- eBayes (m, trend=TRUE, robust=TRUE)
-        }else{
-          m <- eBayes (m, robust=TRUE)
-        }
+        #one-sample t-test is only run for ratio data
+        m <- eBayes (m, robust=TRUE)
         ##at('here4 ')
         sig <- topTable (m, number=nrow(data), sort.by='none')
         ##cat('here5 ')