Citation added.

README.md

@@ -41,4 +41,5 @@ Rscript  /path_to_the_program/ODA.R  /input_path/your_data_file.xlsx  /output_pa
 6. Interested_and_Excluded_Features: If you supply a list of features e.g. significant features by differential intensity tests, the program can generate plots and result sheet for selected features only. The program can also exclude features from analysis if you supply a list. This example shows you how to specify those lists.
 7. List_Data: The program supports raw data in a table (features in rows and samples in columns) or list (features, samples, and values each in a column). While the above examples are all in the table format, this example shows you how to supply data in the list format.
 
+Citation: DeVilbiss AW, Zhao Z, Martin-Sandoval MS, Ubellacker JM, Tasdogan A, Agathocleous M, Mathews TP, Morrison SJ. Metabolomic profiling of rare cell populations isolated by flow cytometry from tissues. eLife 2021;10:e61980.[PMCID: PMC7847306](http://www.ncbi.nlm.nih.gov/pmc/articles/pmc7847306/)
 Contact [Zhiyu Zhao](mailto:zhiyu.zhao@utsouthwestern.edu) for comments / questions / suggestions.

V1.7.3/ODA.R

@@ -121,6 +121,8 @@ visual=T	#Whether to visualize data using graphs.
 volcanoP='adjusted p-value'	#Which p-value as the y-axis of volcano plots.
 hclustSamples=T	#Whether to cluster samples on the heatmap.
 hclustFeatures=T	#Whether to cluster features on the heatmap.
+pcaLabels=T
+pcaEllipses=T
 colors=c('Red','Yellow','Blue','Orange','Green','Purple','Magenta','Cyan','Gray','Black')
 heatmapColors=colorRampPalette(c('blue','white','red'))(256)
 #############################End Default Settings#############################
@@ -193,6 +195,14 @@ if ('Parameters' %in% sheetNames) {
 			hclustSamples=F
 		if (!is.na(parameters[15,1])&&parameters[15,1]=='No')
 			hclustFeatures=F
+		if (!is.na(parameters[16,1])&&parameters[16,1]=='Red and Green')
+			heatmapColors=colorRampPalette(c('green','black','red'))(256)
+		if (!is.na(parameters[16,1])&&parameters[16,1]=='Black and White')
+			heatmapColors=gray.colors(256,0,1)
+		if (!is.na(parameters[17,1])&&parameters[17,1]=='No')
+			pcaLabels=F
+		if (!is.na(parameters[18,1])&&parameters[18,1]=='No')
+			pcaEllipses=F
 	}
 } else
 	stop('Parameter sheet is missing.')
@@ -517,7 +527,11 @@ for (plotType in plotTypes) {
 				plotFile=file.path(figuresPath,paste0(plotType,'_pca_cor.ps'))
 				plotFile2=file.path(figuresPath,paste0(plotType,'_pca_cor.png'))
 				plotData=data.frame(prcomp(t(tempData))$x,sampleIDs)
-				p1=ggplot(plotData,aes(x=PC1,y=PC2,color=GroupID))+geom_point(aes(shape=BatchID))+stat_ellipse(type="norm")+geom_text(aes(label=rownames(plotData),vjust = "inward", hjust = "inward"))+ggtitle(paste0('PCA of ',titleText))
+				p1=ggplot(plotData,aes(x=PC1,y=PC2,color=GroupID))+geom_point(aes(shape=BatchID))+ggtitle(paste0('PCA of ',titleText))
+				if (pcaLabels)
+					p1=p1+geom_text(aes(label=rownames(plotData),vjust = "inward", hjust = "inward"))
+				if (pcaEllipses)
+					p1=p1+stat_ellipse(type="norm")
 				if (dim(tempData)[1]>2)
 					pMat=cor_pmat(tempData)
 				else