From 8d995a81c972c7c78a1075e9dc90fb8033e9b7dc Mon Sep 17 00:00:00 2001
From: Alexis  CRISCUOLO <alexis.criscuolo@pasteur.fr>
Date: Wed, 27 May 2020 09:44:34 +0200
Subject: [PATCH] 0.1

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 91f426a..35ec151 100644
--- a/README.md
+++ b/README.md
@@ -168,7 +168,7 @@ nAUC aWallace2          0.999118  [0.996141 , 1.000000]
 The clustering based on the cutoff 0.007 seems robust to data subsampling, as the three estimated nAUC are quite high (e.g. > 0.75).
 However, the same clustering seems less robust to data perturbation, as the 2.5% CI are quite small for the silhouette and the first Wallace coefficient, e.g. < 0.4.
 
-**Searching optimal clustering**
+**Searching for optimal clustering**
 
 An optimal MST-based clustering can be defined by the cutoff value that maximizes the different estimated statistics.
 By considering every branch length from the minimum spanning tree in _data.graphml_ (see above) as a putative cutoff, _MSTclust_ can be used to display in standard output these statistics in a convenient tab-delimited format (option `-t`):
-- 
GitLab