OpenMS · t0mdavid-m · Sep 27, 2026 · Sep 27, 2026 · Sep 28, 2026
diff --git a/.github/workflows/build-windows-executable-app.yaml b/.github/workflows/build-windows-executable-app.yaml
@@ -336,7 +336,7 @@ jobs:
 
         Reach out to us:
         - Join our Discord server for support and community discussions: https://discord.com/invite/4TAGhqJ7s5
-        - Contribute or stay updated with the latest OpenMS web app developments on GitHub: https://github.com/OpenMS/streamlit-template
+        - Contribute or stay updated with the latest OpenDDA developments on GitHub: https://github.com/OpenMS/quantms-web
         - Visit our website for more information: https://openms.de/
 
         Thank you for using ${{ env.APP_NAME }}!

diff --git a/.github/workflows/test-win-exe-w-embed-py.yaml b/.github/workflows/test-win-exe-w-embed-py.yaml
@@ -84,7 +84,7 @@ jobs:
 
           Reach out to us:
           - Join our Discord server for support and community discussions: https://discord.com/invite/4TAGhqJ7s5
-          - Contribute or stay updated with the latest OpenMS web app developments on GitHub: https://github.com/OpenMS/streamlit-template
+          - Contribute or stay updated with the latest OpenDDA developments on GitHub: https://github.com/OpenMS/quantms-web
           - Visit our website for more information: https://openms.de/
 
           Thank you for using ${{ env.APP_NAME }}!

diff --git a/Dockerfile b/Dockerfile
@@ -14,7 +14,7 @@ ARG PORT=8501
 # Streamlit app GitHub user name (to download artifact from).
 ARG GITHUB_USER=OpenMS
 # Streamlit app GitHub repository name (to download artifact from).
-ARG GITHUB_REPO=streamlit-template
+ARG GITHUB_REPO=quantms-web
 
 USER root
 

diff --git a/Dockerfile.arm b/Dockerfile.arm
@@ -14,7 +14,7 @@ ARG PORT=8501
 # Streamlit app GitHub user name (to download artifact from).
 ARG GITHUB_USER=OpenMS
 # Streamlit app GitHub repository name (to download artifact from).
-ARG GITHUB_REPO=streamlit-template
+ARG GITHUB_REPO=quantms-web
 
 USER root
 

diff --git a/Dockerfile_simple b/Dockerfile_simple
@@ -14,7 +14,7 @@ ARG PORT=8501
 # Streamlit app GitHub user name (to download artifact from).
 ARG GITHUB_USER=OpenMS
 # Streamlit app GitHub repository name (to download artifact from).
-ARG GITHUB_REPO=streamlit-template
+ARG GITHUB_REPO=quantms-web
 
 
 # Step 1: set up a sane build system

diff --git a/Dockerfile_simple.arm b/Dockerfile_simple.arm
@@ -14,7 +14,7 @@ ARG PORT=8501
 # Streamlit app GitHub user name (to download artifact from).
 ARG GITHUB_USER=OpenMS
 # Streamlit app GitHub repository name (to download artifact from).
-ARG GITHUB_REPO=streamlit-template
+ARG GITHUB_REPO=quantms-web
 
 
 # Step 1: set up a sane build system

diff --git a/content/quickstart.py b/content/quickstart.py
@@ -1,8 +1,8 @@
 """
-DDA Label-Free Quantification Quickstart Page.
+OpenDDA Quickstart Page.
 
-This page provides an overview of the DDA-LFQ workflow and guidance
-for getting started with the analysis pipeline.
+This page provides an overview of the DDA quantification workflows (label-free
+and TMT) and guidance for getting started with the analysis pipeline.
 """
 
 from pathlib import Path
@@ -27,7 +27,7 @@ def render_windows_download_box(app_bytes: bytes) -> None:
     st.markdown(
         """
         <h4 style="color: #6c757d; margin-bottom: 1rem; font-size: 1.3rem; font-weight: 600; text-align: center;">
-            Want to run free and open DDA analysis offline?
+            Want to run free and open DDA analysis (LFQ and TMT) offline?
         </h4>
         """,
         unsafe_allow_html=True,
@@ -93,40 +93,64 @@ def render_windows_download_box(app_bytes: bytes) -> None:
 
 page_setup(page="main")
 
-st.markdown("# DDA Label-Free Quantification")
+st.markdown("# OpenDDA: DDA Quantitative Proteomics")
 
 windows_app_bytes = load_windows_app_bytes()
 if windows_app_bytes is not None:
     render_windows_download_box(windows_app_bytes)
 
 st.markdown(
     """
-This application provides a complete **Data-Dependent Acquisition (DDA) Label-Free Quantification**
-workflow for proteomics data analysis. The pipeline enables identification and quantification of
-proteins from mass spectrometry data.
+This application provides complete **Data-Dependent Acquisition (DDA)** quantification
+workflows for proteomics data analysis. The pipeline identifies and quantifies proteins
+from mass spectrometry data and supports two quantification strategies:
+
+- **Label-free quantification (LFQ)**: compares precursor intensities across separately measured samples.
+- **Tandem Mass Tag (TMT) quantification**: compares reporter-ion intensities of multiplexed samples measured in one run.
+
+Choose the **Analysis Mode** (LFQ or TMT) on the Configure page.
 """
 )
 
 st.info(
-    "This workflow mirrors the **dda-lfq branch of the quantms Nextflow workflow** "
-    "for DDA-based label-free quantification."
+    "These workflows mirror the **DDA-LFQ and DDA-ISO (TMT) branches of the quantms Nextflow workflow**."
 )
 
 st.markdown("## Workflow Overview")
 
-st.markdown(
-    """
-The analysis pipeline consists of five main stages:
-
-| Stage | Tool | Description |
-|-------|------|-------------|
-| **1. Identification** | Comet | Peptide-spectrum matching using a protein database |
-| **2. Rescoring** | Percolator | Statistical validation using machine learning |
-| **3. Filtering** | IDFilter | FDR-controlled filtering of identifications |
-| **4. Quantification** | ProteomicsLFQ | Label-free quantification across samples |
-| **5. Statistical Analysis** | Built-in | Volcano plots, PCA, and heatmaps |
+lfq_col, tmt_col = st.columns(2)
+
+with lfq_col:
+    st.markdown(
+        """
+### Label-free (LFQ)
+
+| Stage | Tool |
+|-------|------|
+| **1. Identification** | Comet |
+| **2. Rescoring** | Percolator |
+| **3. Filtering** | IDFilter |
+| **4. Quantification** | ProteomicsLFQ |
+| **5. Statistical Analysis** | Built-in |
 """
-)
+    )
+
+with tmt_col:
+    st.markdown(
+        """
+### TMT
+
+| Stage | Tool |
+|-------|------|
+| **1. Reporter extraction** | IsobaricAnalyzer |
+| **2. Identification** | Comet |
+| **3. Rescoring** | Percolator |
+| **4. Filtering** | IDFilter |
+| **5. Protein inference** | ProteinInference |
+| **6. Quantification** | ProteinQuantifier |
+| **7. Statistical Analysis** | Built-in |
+"""
+    )
 
 st.markdown("## Getting Started")
 
@@ -143,7 +167,7 @@ def render_windows_download_box(app_bytes: bytes) -> None:
 st.markdown(
     """
 ### 2. Configure Parameters
-Set up search parameters, sample groups, and analysis settings.
+Choose LFQ or TMT, then set up search parameters, sample groups (or TMT channels), and analysis settings.
 """
 )
 st.page_link("content/workflow_configure.py", label="Go to Configure", icon="⚙️")

diff --git a/settings.json b/settings.json
@@ -1,8 +1,8 @@
 {
-    "app-name": "quantms-web (DDA-LFQ)",
+    "app-name": "OpenDDA",
     "github-user": "OpenMS",
     "version": "1.1",
-    "repository-name": "streamlit-template",
+    "repository-name": "quantms-web",
     "legal_links": {
         "impressum": "https://openms.de/impressum",
         "privacy": "https://openms.de/privacy",