Updated Readme

README.md

@@ -1,11 +1,13 @@
 
 [![Travis build status](https://travis-ci.org/enriquea/feseR.svg?branch=master)](https://travis-ci.org/enriquea/feseR)
 
+
 # feseR: Feature Selection in R
 
+
 ## Introduction
 
-We provide here a R package which combine multiple Feature Selection (FS) methods in a workflow for analizing high-dimentional omics data. The different feature selection steps can be classificated in: i) Univariate (Correlation filter and Gain Information), ii) Multivariate (Principal Component Analysis and Matrix Correlation based) and iii) Recursive Feature Elimination (wrapped up with a Machine Learning algorithm, i.e. Random Forest). The goal is to essemble the different steps in a efficient workflow to perform feature selection task in the contex of classification and regression problems.
+We provide here a R package which combine multiple Feature Selection (FS) methods in a workflow for analizing high-dimentional omics data. The different feature selection steps can be classificated in: i) Univariate (Correlation filter and Gain Information), ii) Multivariate (Principal Component Analysis and Matrix Correlation based) and iii) Recursive Feature Elimination (wrapped up with a Machine Learning algorithm, e.g. Random Forest). The goal is to essemble the different steps in an efficient workflow to perform feature selection in the contex of classification and regression problems.
 
 ## How to install
 
@@ -16,7 +18,7 @@ The first step is to install `devtools`:
 
 Then, we can install the package using: 
 
-    install_github("drychkov/feseR")
+    install_github("enriquea/feseR")
     library(feseR)
 
 
@@ -32,3 +34,11 @@ Enrique Audain, Yassel Ramos, Henning Hermjakob, Darren R. Flower, Yasset Perez-
 
 If you find useful this tool in your work, you could want citing us:
 Perez-Riverol Y, Kuhn M, Vizcaíno JA, Hitz M-P, Audain E (2017) Accurate and fast feature selection workflow for high-dimensional omics data. PLoS ONE 12(12): e0189875. https://doi.org/10.1371/journal.pone.0189875
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+## Mainteiner
+
+Enrique Audain 
+
+Dmitry Rychkov 
+
+Yasset Perez-Riverol