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+++ b/README.md
@@ -1,118 +1,114 @@
-<!-- badges: start -->
-  [![R-CMD-check](https://github.com/yigbt/multiGSEA/actions/workflows/test.yaml/badge.svg)](https://github.com/yigbt/multiGSEA/actions/workflows/test.yaml)
-  <!-- badges: end -->
-
-
-# The `multiGSEA` `R` package
-
-## Authors
-
-Sebastian Canzler and Jörg Hackermüller
-
-[multiGSEA: a GSEA-based pathway enrichment analysis for multi-omics data](https://doi.org/10.1186/s12859-020-03910-x), _BMC Bioinformatics_ 21, 561 (2020)
-
-## Introduction
-
-The `multiGSEA` package was designed to run a robust GSEA-based
-pathway enrichment for multiple omics layers. The enrichment is
-calculated for each omics layer separately and aggregated p-values are
-calculated afterwards to derive a composite multi-omics pathway
-enrichment.
-
-Pathway definitions can be downloaded from up to eight different
-pathway databases by means of the
-[`graphite`](http://bioconductor.org/packages/release/bioc/html/graphite.html)
-Bioconductor package.
-
-Features of the transcriptome and proteome level can be mapped to the
-following ID formats:
-
-	* Entrez Gene ID
-	* Uniprot IDs
-	* Gene Symbols
-	* RefSeq
-	* Ensembl
-	
-Features of the metabolome layer can be mapped to:
-
-	* Comptox Dashboard IDs (DTXCID, DTXSID)
-	* CAS-RN numbers
-	* Pubchem IDs (CID)
-	* HMDB IDs
-	* KEGG IDs
-	* ChEBI IDs
-	* Drugbank IDs
-	* Common names
-
-  
-Please note, that the mapping of metabolite IDs is accomplished
-through the `metaboliteIDmapping` package.  This `AnnotationHub`
-package provides a comprehensive mapping table with more than one
-million compounds (`metaboliteIDmapping` on our [github
-page](https://github.com/yigbt/metaboliteIDmapping) or at
-[Bioconductor](http://bioconductor.org/packages/metaboliteIDmapping/)).
-  
-  
-## Installation
-
-There are two ways to install the `multiGSEA` package. For both you
-have to install and start R in at least version 4.0:
-
-(i) Use the Bioconductor framework:
-
-```R
-if (!requireNamespace("BiocManager", quietly = TRUE))
-  install.packages("BiocManager")
-
-BiocManager::install("multiGSEA")
-```
-
-(ii) Alternatively, you can install the most up to date version
-(development) easily with
-[devtools](https://github.com/hadley/devtools):
-
-```R
-install.packages("devtools")
-devtools::install_github("https://github.com/yigbt/multiGSEA")
-```
-
-Once installed, just load the `multiGSEA` package with:
-
-```R
-library(multiGSEA)
-```
-
-
-# Workflow
-
-A common workflow is exemplified in the package vignette and is
-typically separated in the following steps:
-
-1. Load required libraries, including the `multiGSEA` package, and
-   omics data sets.
-2. Create data structure for enrichment analysis.
-3. Download and customize the pathway definitions.
-4. Run the pathway enrichment for each omics layer.
-5. Calculate the aggregated pathway enrichment.
-
-
-For more information please have a look in the vignette at our
-[Bioconductor
-page](https://bioconductor.org/packages/release/bioc/vignettes/multiGSEA/inst/doc/multiGSEA.html).
-
-
-# LICENSE
-
-Copyright (C) 2011 - 2020 Helmholtz Centre for Environmental Research
-UFZ.
-
-This program is free software: you can redistribute it and/or modify
-it under the terms of the GNU General Public License as published by
-the Free Software Foundation, either version 3 of the License, or (at
-your option) any later version.
-
-This program is distributed in the hope that it will be useful, but
-WITHOUT ANY WARRANTY; without even the implied warranty of
-MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the UFZ
-License document for more details:
-<https://github.com/yigbt/multiGSEA/blob/master/LICENSE.md>
+
+# The `multiGSEA` `R` package
+
+## Authors
+
+Sebastian Canzler and Jörg Hackermüller
+
+[multiGSEA: a GSEA-based pathway enrichment analysis for multi-omics data](https://doi.org/10.1186/s12859-020-03910-x), _BMC Bioinformatics_ 21, 561 (2020)
+
+## Introduction
+
+The `multiGSEA` package was designed to run a robust GSEA-based
+pathway enrichment for multiple omics layers. The enrichment is
+calculated for each omics layer separately and aggregated p-values are
+calculated afterwards to derive a composite multi-omics pathway
+enrichment.
+
+Pathway definitions can be downloaded from up to eight different
+pathway databases by means of the
+[`graphite`](http://bioconductor.org/packages/release/bioc/html/graphite.html)
+Bioconductor package.
+
+Features of the transcriptome and proteome level can be mapped to the
+following ID formats:
+
+	* Entrez Gene ID
+	* Uniprot IDs
+	* Gene Symbols
+	* RefSeq
+	* Ensembl
+	
+Features of the metabolome layer can be mapped to:
+
+	* Comptox Dashboard IDs (DTXCID, DTXSID)
+	* CAS-RN numbers
+	* Pubchem IDs (CID)
+	* HMDB IDs
+	* KEGG IDs
+	* ChEBI IDs
+	* Drugbank IDs
+	* Common names
+
+  
+Please note, that the mapping of metabolite IDs is accomplished
+through the `metaboliteIDmapping` package.  This `AnnotationHub`
+package provides a comprehensive mapping table with more than one
+million compounds (`metaboliteIDmapping` on our [github
+page](https://github.com/yigbt/metaboliteIDmapping) or at
+[Bioconductor](http://bioconductor.org/packages/metaboliteIDmapping/)).
+  
+  
+## Installation
+
+There are two ways to install the `multiGSEA` package. For both you
+have to install and start R in at least version 4.0:
+
+(i) Use the Bioconductor framework:
+
+```R
+if (!requireNamespace("BiocManager", quietly = TRUE))
+  install.packages("BiocManager")
+
+BiocManager::install("multiGSEA")
+```
+
+(ii) Alternatively, you can install the most up to date version
+(development) easily with
+[devtools](https://github.com/hadley/devtools):
+
+```R
+install.packages("devtools")
+devtools::install_github("https://github.com/yigbt/multiGSEA")
+```
+
+Once installed, just load the `multiGSEA` package with:
+
+```R
+library(multiGSEA)
+```
+
+
+# Workflow
+
+A common workflow is exemplified in the package vignette and is
+typically separated in the following steps:
+
+1. Load required libraries, including the `multiGSEA` package, and
+   omics data sets.
+2. Create data structure for enrichment analysis.
+3. Download and customize the pathway definitions.
+4. Run the pathway enrichment for each omics layer.
+5. Calculate the aggregated pathway enrichment.
+
+
+For more information please have a look in the vignette at our
+[Bioconductor
+page](https://bioconductor.org/packages/release/bioc/vignettes/multiGSEA/inst/doc/multiGSEA.html).
+
+
+# LICENSE
+
+Copyright (C) 2011 - 2020 Helmholtz Centre for Environmental Research
+UFZ.
+
+This program is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or (at
+your option) any later version.
+
+This program is distributed in the hope that it will be useful, but
+WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the UFZ
+License document for more details:
+<https://github.com/yigbt/multiGSEA/blob/master/LICENSE.md>