diff --git a/README.md b/README.md
index d97db815b28e5f0b93dcc9e28004ab4cf9b45870..25acd225345ec89ae8fe2dcbf1490a763422ec24 100644
--- a/README.md
+++ b/README.md
@@ -7,7 +7,7 @@ Amodio G, Giacomini G, Boeri L, et al. **T cell exhaustion and senescence signat
 scRNAseq analysis was performed using a standard [Seurat](https://satijalab.org/seurat/) pipeline that includes the following steps starting from a minimal object after loading of 10X data to markers identification:
 
    - Preprocessing and cell filtering
-      - Each sample was pre-processed and cells with mitochondrial RNA percentages higher than 10 and a number of features <1200 or >6000, were filtered out.   
+      - Each sample was pre-processed and cells with mitochondrial RNA percentages higher than 10 and a number of features <1200 or >6000, were filtered out. Samples were merged into a single Seurat dataset  
    - Normalization 
       - Default Seurat settings [(NormalizeData function)](https://satijalab.org/seurat/reference/normalizedata)
    - Scaling: 
@@ -21,6 +21,8 @@ scRNAseq analysis was performed using a standard [Seurat](https://satijalab.org/
 
   
 ### Directories and Files ###
+- sampleSheet.csv: names of samples and corresponding conditions
+
 - **Script**: R scripts used for the analyses
   - `1_PreProcessing_Data.R`: Preprocessing, cell filtering and Full object creation
   - `2_Infertility_scRNAseq_analysis.R`: