From b6962b4b72c6c2343e929b3e6e656f5345598a3c Mon Sep 17 00:00:00 2001
From: Arnaud Duvermy <arnaud.duvermy@ens-lyon.fr>
Date: Thu, 10 Feb 2022 16:54:28 +0100
Subject: [PATCH] Update README.md

---
 README.md | 10 +++++++---
 1 file changed, 7 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index 680e2ca..a89c644 100644
--- a/README.md
+++ b/README.md
@@ -37,16 +37,20 @@ where counts K ij for gene i, sample j are modeled using a Negative Binomial dis
 fitted mean µ ij and a gene-specific dispersion parameter α i . The fitted mean is composed of a
 sample-specific size factor s j and a parameter q ij proportional to the expected true concentration of fragments for sample j. The coefficients β i give the log2 fold changes for gene i for each column of the model matrix X. <br/>
 
-### 4) Wald Test H0: 
+### 4) Wald Test: 
 
-Test if Log(FC) = 0 <br/>
+H0: Test if Log(FC) = 0 <br/>
 
 With DESeq2, the Wald test is the default used for hypothesis testing when comparing two groups. The Wald test is a test of hypothesis usually performed on parameters that have been estimated by maximum likelihood. The Wald test is also a standard way to extract a P value from a regression fit.
 
 
 ## Investigations
 
-Let µ and alpha constant between samples, replicates and genes 
+
+N.B: Don't forget to change your home path in ```src/main.R```
+
+
+Let µ and alpha constant between samples, replicates and genes (absolutely false IRL)
 
 1) µ effect 
 
-- 
GitLab