From a7e538e56238ac74a55ddd41e4ed544d662da8fd Mon Sep 17 00:00:00 2001
From: "Matthijs S. Berends" <berendsms@gmail.com>
Date: Sat, 30 Nov 2019 13:31:12 +0100
Subject: [PATCH] (v0.9.0) website fixes

---
 R/mo_source.R   | 2 +-
 docs/index.html | 2 +-
 index.md        | 2 +-
 3 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/R/mo_source.R b/R/mo_source.R
index 8b054964..58fcc4b2 100644
--- a/R/mo_source.R
+++ b/R/mo_source.R
@@ -216,5 +216,5 @@ mo_source_isvalid <- function(x) {
   if (!"mo" %in% colnames(x)) {
     return(FALSE)
   }
-  all(x$mo %in% c("", AMR::microorganisms$mo, AMR::microorganisms.translation$mo_old), na.rm = TRUE)
+  all(x$mo %in% c("", AMR::microorganisms$mo, microorganisms.translation$mo_old), na.rm = TRUE)
 }
diff --git a/docs/index.html b/docs/index.html
index 82f6284c..a16635e8 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -199,7 +199,7 @@ A methods paper about this package has been preprinted at bioRxiv. It was update
 <h3 class="hasAnchor">
 <a href="#what-is-amr-for-r" class="anchor"></a>What is <code>AMR</code> (for R)?</h3>
 <p><em>(<help title="Too Long, Didn't Read">TLDR</help> - to find out how to conduct AMR analysis, please <a href="./articles/AMR.html">continue reading here to get started</a>.</em></p>
-<p><code>AMR</code> is a <strong>free and open-source</strong> <a href="https://www.r-project.org">R package</a> to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods. Our aim is to offer a new standard for clean and reproducible antimicrobial resistance data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.</p>
+<p><code>AMR</code> is a free and open-source <a href="https://www.r-project.org">R package</a> to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. <strong>Our aim is to supply a standard</strong> for clean and reproducible antimicrobial resistance data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.</p>
 <p>After installing this package, R knows <a href="./reference/microorganisms.html"><strong>~70,000 distinct microbial species</strong></a> and all <a href="./reference/antibiotics.html"><strong>~550 antibiotic, antimycotic and antiviral drugs</strong></a> by name and code, and knows all about valid RSI and MIC values. It supports any data format, including WHONET/EARS-Net data.</p>
 <p>We created this package for both routine analysis and academic research (as part of our PhD theses) at the Faculty of Medical Sciences of the University of Groningen, the Netherlands, and the Medical Microbiology &amp; Infection Prevention (MMBI) department of the University Medical Center Groningen (UMCG). This R package is <a href="./news">actively maintained</a> and is free software (see <a href="#copyright">Copyright</a>).</p>
 <div class="main-content"> 
diff --git a/index.md b/index.md
index 09c427de..97db68e4 100644
--- a/index.md
+++ b/index.md
@@ -8,7 +8,7 @@
 
 *(<help title="Too Long, Didn't Read">TLDR</help> - to find out how to conduct AMR analysis, please [continue reading here to get started](./articles/AMR.html).*
 
-`AMR` is a **free and open-source** [R package](https://www.r-project.org) to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods. Our aim is to offer a new standard for clean and reproducible antimicrobial resistance data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.
+`AMR` is a free and open-source [R package](https://www.r-project.org) to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. **Our aim is to supply a standard** for clean and reproducible antimicrobial resistance data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.
 
 After installing this package, R knows [**~70,000 distinct microbial species**](./reference/microorganisms.html) and all [**~550 antibiotic, antimycotic and antiviral drugs**](./reference/antibiotics.html) by name and code, and knows all about valid RSI and MIC values. It supports any data format, including WHONET/EARS-Net data.