Update README.md

README.md

 # Amodio_Infertility_2024
 Amodio G, Giacomini G, Boeri L, et al. **T cell exhaustion and senescence signatures characterize and differentiate infertile men**
 
-### Analyses ###
-Single-cell (from 10X Genomics) analysis of CD3+ T cells purified from the peripheral blood of men diagnosed with oligo-astheno-teratozoospermia (OAT, n=4), idiopathic non-obstructive azoospermia (iNOA, n=6), and a control group (FER, n=5).
+### Single-Cell RNA Sequencing Analysis ###
+**scRNAseq** (from 10X Genomics) analysis of CD3+ T cells purified from the peripheral blood of men diagnosed with oligo-astheno-teratozoospermia (OAT, n=4), idiopathic non-obstructive azoospermia (iNOA, n=6), and a control group (FER, n=5).
 
- 
-
-**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:
+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.   
    - Normalization 
-      - Default seurat settings [vignette]
+      - Default Seurat settings ([NormalizeData function])(https://satijalab.org/seurat/reference/normalizedata)
    - Scaling: 
       - Data was regressed out by passing UMI count, the percentage of mitochondrial genes, the difference between the cell cycle phases scores.
    - Dimensionality reduction and Harmony batch removal:
@@ -22,10 +20,9 @@ Single-cell (from 10X Genomics) analysis of CD3+ T cells purified from the perip
       - Intra-cluster comparisons
 
   
-
 ### Directories and Files ###
 - **Script**: R scripts used for the analyses
-  - `1_PreProcessing_Data.R`: Full object creation
+  - `1_PreProcessing_Data.R`: Preprocessing, cell filtering and Full object creation
   - `2_Infertility_scRNAseq_analysis.R`: 
   - `3_SubsetAnalysis_Annotations.R`: subset analyses of T cells and cluster manual annotation
   - `4_ScoreAnalysis_TcellSubset.R`: