diff --git a/README.md b/README.md
index 54b3faf..7be3274 100644
--- a/README.md
+++ b/README.md
@@ -5,7 +5,7 @@ The main steps of the workflow involve:
 1. Mapping each barcode to insertion location in the genome.
 2. Profiling barcode abundances across samples.
 3. Mutant fitness analyses.
-4. Exploratory analysis using [mBARq web app]([https://mbarq-app.herokuapp.com/](https://microbiomics.io/tools/mbarq-app/))
+4. Exploratory analysis using [mBARq web app](https://microbiomics.io/tools/mbarq-app/)
 
 ## Installation:
 
diff --git a/docs/explore.md b/docs/explore.md
index fd1aef0..743ab83 100644
--- a/docs/explore.md
+++ b/docs/explore.md
@@ -1,7 +1,7 @@
 # Explore
 
 
-[mBARq Web App](https://mbarq-app.herokuapp.com/) allows quick and easy interactive exploration of your BarSeq experiment. 
+[mBARq Web App](https://microbiomics.io/tools/mbarq-app/) allows quick and easy interactive exploration of your BarSeq experiment. 
 
 
 ## Visualise barcode positions across the genome
diff --git a/docs/index.rst b/docs/index.rst
index 9c552c2..66feace 100644
--- a/docs/index.rst
+++ b/docs/index.rst
@@ -21,7 +21,7 @@ The main steps of the workflow involve:
 3. Mutant fitness analyses.
 4. Exploratory analysis using `mBARq web app`_
 
-.. _mBARq web app: https://mbarq-app.herokuapp.com/
+.. _mBARq web app: https://microbiomics.io/tools/mbarq-app
 
 
 .. include:: install.md
diff --git a/docs/salmonella.md b/docs/salmonella.md
index 09e75ff..010bb7a 100644
--- a/docs/salmonella.md
+++ b/docs/salmonella.md
@@ -128,7 +128,7 @@ mkdir results
 mbarq analyze -i library_11_1_mbarq_merged_counts.csv -s sample_data.csv -c control_strains.csv --treatment_column day --baseline d0 -o results 
 
 ```
-`mbarq analyze` creates a folder containing `library_11_1_mbarq_merged_counts_rra_results.csv` that lists log fold changes (LFC) and false discovery rates (FDR) for each gene in the library. You can upload this file to the [mBARq App](https://mbarq-app.herokuapp.com/) to create heatmaps, perform functional analysis, and visualize the results in the context of KEGG metabolic maps.
+`mbarq analyze` creates a folder containing `library_11_1_mbarq_merged_counts_rra_results.csv` that lists log fold changes (LFC) and false discovery rates (FDR) for each gene in the library. You can upload this file to the [mBARq App](https://microbiomics.io/tools/mbarq-app/) to create heatmaps, perform functional analysis, and visualize the results in the context of KEGG metabolic maps.