diff --git a/.gitignore b/.gitignore
index 5b6a0652566d10360493952aec6d4a4febc77083..3e2e76369f65d3f9dd008f77e90be904b061ed13 100644
--- a/.gitignore
+++ b/.gitignore
@@ -2,3 +2,4 @@
 .Rhistory
 .RData
 .Ruserdata
+VarExp.Rproj
diff --git a/README.Rmd b/README.Rmd
index 4c252ff7712664decd88ffef47fab510826d3e84..8309e3daadb82bd0414e5c892785ac1376c188c4 100644
--- a/README.Rmd
+++ b/README.Rmd
@@ -7,12 +7,16 @@ knitr::opts_chunk$set(echo = TRUE)
 
 The R package **VarExp** provides functions for the estimating of the percentage of phenotypic variance explained by genetic effects, interaction effects or jointly by both effects. This suite of functions are useful for meta-analysis designs where pooling individual genotype data is challenging. A pre-print article related to this work is available [here](bioRkiv link)
 
+## Prerequisite
+
+Library [**Rcurl**](https://cran.r-project.org/web/packages/RCurl/index.html) is required to run **VarExp**
+
 ## Installation
 
-Install the development version of **VarExp** from GitHub by typing:
+For now, **VarExp** can be installed only using package source. In R, after setting your working directory to *VarExp_0.1.0.tar.gz* location, type:
 
 ```r
-devtools::install_github("vincela/VarExp")
+install.packages("VarExp_0.1.0.tar.gz", repos = NULL, type = "source")
 ```
 
 ## Input format
@@ -55,7 +59,7 @@ Data used in this tutorial are included in the ***VarExp*** package.
 
 ```r
 # Load the package
-library(VarExp2)
+library(VarExp)
 
 # Load the meta-analysis summary statistics file
 data(GWAS)
diff --git a/README.html b/README.html
index abdef278096e0d176d345a6670a0d0375a72d9b7..e363729acaa01c7bbc0bd03c1f8b6ce7edd4e1c2 100644
--- a/README.html
+++ b/README.html
@@ -122,10 +122,14 @@ $(document).ready(function () {
 <div id="varexp" class="section level1">
 <h1>VarExp</h1>
 <p>The R package <strong>VarExp</strong> provides functions for the estimating of the percentage of phenotypic variance explained by genetic effects, interaction effects or jointly by both effects. This suite of functions are useful for meta-analysis designs where pooling individual genotype data is challenging. A pre-print article related to this work is available <a href="bioRkiv%20link">here</a></p>
+<div id="prerequisite" class="section level2">
+<h2>Prerequisite</h2>
+<p>Library <a href="https://cran.r-project.org/web/packages/RCurl/index.html"><strong>Rcurl</strong></a> is required to run <strong>VarExp</strong></p>
+</div>
 <div id="installation" class="section level2">
 <h2>Installation</h2>
-<p>Install the development version of <strong>VarExp</strong> from GitHub by typing:</p>
-<pre class="r"><code>devtools::install_github(&quot;vincela/VarExp&quot;)</code></pre>
+<p>For now, <strong>VarExp</strong> can be installed only using package source. In R, after setting your working directory to <em>VarExp_0.1.0.tar.gz</em> location, type:</p>
+<pre class="r"><code>install.packages(&quot;VarExp_0.1.0.tar.gz&quot;, repos = NULL, type = &quot;source&quot;)</code></pre>
 </div>
 <div id="input-format" class="section level2">
 <h2>Input format</h2>
@@ -176,7 +180,7 @@ $(document).ready(function () {
 <h2>Short tutorial</h2>
 <p>Data used in this tutorial are included in the <strong><em>VarExp</em></strong> package.</p>
 <pre class="r"><code># Load the package
-library(VarExp2)
+library(VarExp)
 
 # Load the meta-analysis summary statistics file
 data(GWAS)
@@ -211,7 +215,11 @@ fracJ    &lt;- calculateVarFrac(std_betaG, std_betaI, C, parsY[2], sum(COHORT$PH
 </div>
 <div id="code-of-conduct" class="section level2">
 <h2>Code of conduct</h2>
-<p>Please note that this project is released with a <a href="link%20to%20file">Contributor Code of Conduct</a>. By participating in this project you agree to abide by its terms.</p>
+<p>Please note that this project is released with a <a href="https://github.com/vincenla/VarExp/code-of-conduct.md">Contributor Code of Conduct</a>. By participating in this project you agree to abide by its terms.</p>
+</div>
+<div id="license" class="section level2">
+<h2>License</h2>
+<p>This project is licensed under the MIT License - see the <a href="https://github.com/vincentla/VarExp/">LICENSE.md</a> file for details</p>
 </div>
 </div>
 
diff --git a/man/COHORT.Rd b/man/COHORT.Rd
index 2c8f247b2147ffb60cfa8db8e119755b572dce07..539c74234c6c741507c3327723ecb5a61f21690f 100644
--- a/man/COHORT.Rd
+++ b/man/COHORT.Rd
@@ -4,7 +4,7 @@
 \name{COHORT}
 \alias{COHORT}
 \title{Example of cohort description input file}
-\format{An object of class \code{data.frame} with 5 rows and 7 columns.}
+\format{An object of class \code{data.frame} with 5 rows and 6 columns.}
 \usage{
 COHORT
 }
diff --git a/man/GWAS.Rd b/man/GWAS.Rd
index 378be4035b5b8d7899ceb69b8ca6f34a552dfbf7..a9788203f471e000e829978e887224637578bb50 100644
--- a/man/GWAS.Rd
+++ b/man/GWAS.Rd
@@ -4,7 +4,7 @@
 \name{GWAS}
 \alias{GWAS}
 \title{Example of GWAS result input file}
-\format{An object of class \code{data.frame} with 15 rows and 13 columns.}
+\format{An object of class \code{data.frame} with 10 rows and 7 columns.}
 \usage{
 GWAS
 }