diff --git a/README.md b/README.md
index 4c64070..f2d2fe9 100644
--- a/README.md
+++ b/README.md
@@ -4,38 +4,44 @@
 * R (packages: edgeR)
 * Python (packages: pandas)
 
-## Running step wise
+## RNASeq Pipeline: 
+Following series of steps show how to run the DDR method on RNASeq data. 
 
 ### Step0 Preprocess
+Step0 should be used to format the count table such that the input table has the gene expression table with first n columns as group1 samples (Triple negative:TN) and remaining columns as samples from group2 (other:OT). Rows represent the ENSG ids.
 ```
 Rscript step0_preprocess.R
 ```
 ### Step1 Calculate Stats
-#### Based on the source of input file, enter RNASeq or microarray as input argument.
+In this step, the count table is normalized and the covariance, standard deviation, mean and MFC are being calculated.
 ```
 Rscript step1_calculateStats.R RNASeq
-Rscript step1_calculateStats.R microarray 
 
 ```
 ### Step2 Find Reference set
-#### Based on the source of input file, enter RNASeq or microarray as input argument.
-
+In this step, reference set of genes are being determined. The output file 'ref_cpm.csv' stores expression level of these reference genes.
 ```
 Rscript step2_findRef.R RNASeq
-Rscript step2_findRef.R microarray
 
 ```
 ### Step3 Find overlap using Fisher's Exact test
 #### Enter number of samples in first group as first input argument.
-#### Based on the source of input file, enter RNASeq or microarray as second input argument.
-
 Since the example dataset has 115 samples in group1.
 ```
 Rscript step3_overlapFisher.R 115 RNASeq
-Rscript step3_overlapFisher.R 115 microarray
-
 ```
 
+## Output files
+* final_out.csv: Normalized count data
+* ref_cpm.csv: Expression of reference genes
+* overlap_test_fdr_1_[RNASeq|microarray].csv or : Differentially expressed genes with fdr < 0.1
+* overlap_test_fdr_05_[RNASeq|microarray].csv: Differentially expressed genes with fdr < 0.05
+
+## Pipeline for microarray data. Note that the steps are similar to for RNASeq data. 
+Rscript step0_preprocess_microarray.R
+Rscript step1_calculateStats.R microarray 
+Rscript step2_findRef.R microarray
+Rscript step3_overlapFisher.R 115 microarray
 
 ## Running all the steps together 
 ```
@@ -45,9 +51,3 @@ If you have another python version that has pandas:
 ```
 Rscript DDR_Ref.R PYTHON_PATH
 ```
-
-## Output files
-* final_out.csv: Normalized count data
-* ref_cpm.csv: Expression of reference genes
-* overlap_test_fdr_1_[RNASeq|microarray].csv or : Differentially expressed genes with fdr < 0.1
-* overlap_test_fdr_05_[RNASeq|microarray].csv: Differentially expressed genes with fdr < 0.05