V2.2:10242024

README.md

@@ -4,9 +4,11 @@ This is an R program to visualize and analyze -omics data such as those from mic
 
 ![FlowChart](FlowChart.png)
 
-## Current version: V2.1. Tested R version: 4.3.2.
+## Current version: V2.2. Tested R version: 4.3.2.
 
-**Highlighted changes:** Metabolite Set Enrichment Analysis (MSEA), Pathway Analysis (MSPA), and Joint-Pathway Analysis (JointPA) are implemented using MetaboAnalystR 3.0.3. If a list of metabolite IDs is supplied, the Over Representation Analysis (ORA) can be done. If a differential test is specified, the Quantitative Enrichment Analysis (QEA) can be done. To do the analysis, metabolites need to be HMDB IDs or KEGG IDs. Alternatively, features can be metabolite names available in the MetaboAnalyst's compound database. See [MetaboAnalyst](https://www.metaboanalyst.ca/) for details about MSEA, MSPA, and JointPA.
+**Highlighted changes in V2.2:** Bulk RNA-seq analysis starting from a raw count table was added. DESeq2 is used for bulk RNA-seq data normalization and differential tests. clusterProfiler ORA and QEA analyses were added for gene/protein data. PLS-DA plot was added. Spearman and Kendall correlation plots were added. Analysis without erasing previous results was enabled.
+
+**Highlighted changes in V2.1:** Metabolite Set Enrichment Analysis (MSEA), Pathway Analysis (MSPA), and Joint-Pathway Analysis (JointPA) were implemented using MetaboAnalystR 3.0.3. If a list of metabolite IDs is supplied, the Over Representation Analysis (ORA) can be done. If a differential test is specified, the Quantitative Enrichment Analysis (QEA) can be done. To do the analysis, metabolites need to be HMDB IDs or KEGG IDs. Alternatively, features can be metabolite names available in the MetaboAnalyst's compound database. See [MetaboAnalyst](https://www.metaboanalyst.ca/) for details about MSEA, MSPA, and JointPA.
 
 ## How to run this tool:
 
@@ -18,7 +20,7 @@ This is an R program to visualize and analyze -omics data such as those from mic
 
 **Step 4:** Fill in the ***Parameters***, ***Comparisons***, ***Features***, and ***Samples*** sheets as necessary.
 
-**Step 5:** Run the program with your data and save results in an Excel file. If visualization is enabled, a Figures folder will be created to save the plots in the Portable Network Graphics (.png) and postscript (.ps) formats. See below for ways of running the program.
+**Step 5:** Run the program with your data and save results in an Excel file. If visualization is enabled, a Figures folder will be created to save the plots in the Portable Network Graphics (.png) and postscript (.ps) formats. If enrichment analysis is enabled, an EnrichmentAnalysis folder will be created to save the results. See below for ways of running the program.
 
 1. Running on the BioHPC @ UTSW. Log on the BioHPC ***Portal***, launch a ***Web Visualization*** node, open a terminal from there, and run the following:
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