diff --git a/src/qc/integration_metrics/config.vsh.yaml b/src/qc/integration_metrics/config.vsh.yaml
new file mode 100644
index 00000000000..157f7ff845c
--- /dev/null
+++ b/src/qc/integration_metrics/config.vsh.yaml
@@ -0,0 +1,171 @@
+functionality:
+  name: integration_metrics
+  namespace: "qc"
+  description: |
+    Calculation integration qc metrics and aggregate scores for bio conservation and batch correction.
+    The calculated metrics and aggregate scores are stored in the uns column.
+    All metric calculations are based on the scib library:
+      - publication: https://doi.org/10.1038/s41592-021-01336-8
+      - code: https://github.com/theislab/scib/
+      - documentation: https://scib.readthedocs.io/
+
+    Bio conservation metrics:
+      - nmi_score: scib.metrics.nmi
+      - ari_score: scib.metrics.ari
+      - asw_label: scib.metrics.silhouette
+      - isolated_label_f1: scib.metrics.isolated_labels 
+      - isolated_label_asw: scib.metrics.isolated_labels
+      - clisi_graph: scib.metrics.clisi_graph
+    Note that the scib bio conservation metrics for cell cycle conservation, HVG conservation and trajectory conservation are not currently provided, 
+    as this requires integrated count matrices and pseudo time values to be calculated, which is not currently supported in OpenPipeline.
+
+    Batch correction metrics:
+      - asw_batch: scib.metrics.silhouette_batch
+      - pcr_score: scib.metrics.pcr_comparison
+      - graph_connectivity: scib.metrics.graph_connectivity
+      - ilisi_graph: scib.metrics.ilisi_graph
+      - kbet: scib.metrics.kBET
+
+    Aggregate scores:
+      - avg_bio: mean of calculated bio conservation metrics
+      - avg_batch: mean of calculated batch correction metrics
+      - overall_integration_score: weighted mean of bio and batch scores (60/40 ratio)
+      
+  authors:
+    - __merge__: /src/authors/dorien_roosen.yaml
+      roles: [ author ]
+  argument_groups:
+    - name: Inputs
+      arguments:
+        - name: "--input"
+          type: file
+          description: Input h5mu file
+          direction: input
+          required: true
+          example: input.h5mu
+        - name: "--modality"
+          type: string
+          default: "rna"
+        - name: "--bio_conservation_metrics"
+          type: string
+          multiple: true
+          multiple_sep: ";"
+          choices: 
+            - nmi
+            - ari
+            - asw_label
+            - isolated_label_f1
+            - isolated_label_asw
+            - clisi_graph
+          default: nmi;ari;asw_label
+          description: |
+            The metrics to be calculated to assess biological conservation. 
+            The provided metrics will be aggregated into a biological conservation score.
+        - name: "--batch_correction_metrics"
+          type: string
+          multiple: true
+          multiple_sep: ";"
+          choices:
+            - asw_batch
+            - pcr
+            - graph_connectivity
+            - ilisi_graph
+            - kbet
+          default: asw_batch;pcr;graph_connectivity
+          description: |
+            The metrics to be calculated for the batch correction. 
+            The provided metrics will be aggregated into a batch correction score.
+
+    - name: Input Annotations
+      arguments:
+        - name: "--obsm_embeddings"
+          type: string
+          required: true
+          example: "X_scGPT"
+          description: |
+            The name of the adata.obsm array containing scGPT cell embeddings.
+        - name: "--obs_batch_label"
+          type: string
+          example: "sample"
+          required: true
+          description: |
+            The name of the adata obs column containing the batch labels.
+        - name: "--obs_cell_label"
+          type: string
+          example: "cell_type"
+          required: true
+          description: |
+            The name of the adata obs column containing the cell type labels.
+        - name: "--obs_cluster"
+          type: string
+          example: "cluster"
+          required: true
+          description: |
+            The name of the adata obs column containing the cluster labels.
+        - name: "--uns_neighbors"
+          type: string
+          example: "neighbors"
+          required: true
+          description:
+            The name of the adata uns object containing the neighbors information.
+        - name: "--obsp_neighbor_connectivities"
+          type: string
+          example: "connectivities"
+          required: true
+          description: |
+            The name of the adata obsp object containing the neighbor connectivities.
+
+
+    - name: Outputs
+      arguments:
+        - name: "--output"
+          type: file
+          description: Output h5mu file.
+          direction: output
+          example: output.h5mu
+        - name: "--output_compression"
+          type: string
+          description: The compression format to be used on the output h5mu object.
+          choices: ["gzip", "lzf"]
+          required: false
+          example: "gzip"
+
+  resources:
+    - type: python_script
+      path: script.py
+   
+platforms:
+  - type: docker
+    image: rocker/r2u:22.04
+    setup:
+      - type: apt
+        packages: 
+          - procps
+          - libhdf5-dev
+          - gfortran
+          - cmake
+          - libopenblas-dev
+          - libgeos-dev
+          - python3-pip
+          - python3-dev
+          - python-is-python3
+      - type: python
+        __merge__: [ /src/base/requirements/anndata_mudata.yaml ]
+      - type: python
+        packages:
+          - scib==1.1.5
+          - rpy2==3.5.16
+          - anndata2ri
+      - type: r
+        github: [ theislab/kBET ]
+      - type: docker
+        run: |
+          cd "$(pip show scib | grep Location | cut -d ' ' -f 2)/scib/knn_graph" && \
+          g++ -std=c++11 -O3 knn_graph.cpp -o knn_graph.o
+
+    test_setup:
+      - type: python
+        __merge__: [ /src/base/requirements/viashpy.yaml, .]
+  - type: nextflow
+    directives:
+      label: [singlecpu, lowmem]
\ No newline at end of file
diff --git a/src/qc/integration_metrics/script.py b/src/qc/integration_metrics/script.py
new file mode 100644
index 00000000000..1c4e80a3c01
--- /dev/null
+++ b/src/qc/integration_metrics/script.py
@@ -0,0 +1,274 @@
+import scib
+import mudata as mu
+import numpy as np
+import warnings
+
+## VIASH START
+par = {
+    "input": "resources_test/scgpt/test_resources/Kim2020_Lung_integrated_leiden.h5mu",
+    "modality": "rna",
+    "bio_conservation_metrics": ["nmi","ari","asw_label"],
+    "batch_correction_metrics": ["asw_batch","pcr","graph_connectivity"],
+    "obsm_embeddings": "X_scGPT",
+    "obs_batch_label": "sample",
+    "obs_cell_label": "cell_type",
+    "uns_neighbors": "scGPT_integration_neighbors",
+    "obsp_neighbor_connectivities": "scGPT_integration_connectivities",
+    "output_compression": None,
+    "obs_cluster": "scGPT_integration_leiden_1.0",
+    "output": "resources_test/scgpt/test_resources/Kim2020_Lung_integrated_qc.h5mu",
+}
+
+## VIASH END
+
+# START TEMPORARY WORKAROUND setup_logger
+# reason: resources aren't available when using Nextflow fusion
+# from setup_logger import setup_logger
+def setup_logger():
+    import logging
+    from sys import stdout
+
+    logger = logging.getLogger()
+    logger.setLevel(logging.INFO)
+    console_handler = logging.StreamHandler(stdout)
+    logFormatter = logging.Formatter("%(asctime)s %(levelname)-8s %(message)s")
+    console_handler.setFormatter(logFormatter)
+    logger.addHandler(console_handler)
+
+    return logger
+# END TEMPORARY WORKAROUND setup_logger
+logger = setup_logger()
+
+warnings.filterwarnings("ignore", category=DeprecationWarning)
+warnings.filterwarnings("ignore", category=FutureWarning)
+
+logger.info("Reading in data")
+# Read in data
+mdata = mu.read(par["input"])
+input_adata = mdata.mod[par["modality"]]
+adata = input_adata.copy()
+
+# Remove nan values to calculate scores
+if adata.obs["cell_type"].isna().any():
+    logger.warning("Cell label obs column contains nan values: removing rows with nan value")
+    adata_t = adata[~adata.obs["cell_type"].isna()].copy()
+else:
+    adata_t = adata.copy()
+
+# Ensure all batch labels are str
+adata.obs[par["obs_batch_label"]] = adata.obs[par["obs_batch_label"]].astype(str)
+
+# rename neighbors and connectivities names if necessary
+if par["uns_neighbors"] != "neighbors":
+    adata_t.uns["neighbors"] = adata_t.uns[par["uns_neighbors"]]
+if par["obsp_neighbor_connectivities"] != "connectivities":
+    adata_t.obsp["connectivities"] = adata_t.obsp[par["obsp_neighbor_connectivities"]]
+
+# Asses metrics to be calculated
+assert len(par["bio_conservation_metrics"]) > 0, "Provide at least one metric for bio conservation."
+assert len(par["batch_correction_metrics"]) > 0, "Provide at least one metric for bio conservation."
+
+bio_metric_calc = {
+    "nmi": False,
+    "ari": False,
+    "asw_label": False,
+    "isolated_label_f1": False,
+    "isolated_label_asw": False,
+    "clisi_graph": False,
+}
+
+batch_metric_calc = {
+    "asw_batch": False,
+    "pcr": False,
+    "graph_connectivity": False,
+    "ilisi_graph": False,
+    "kbet": False
+}
+
+for bio_metric in par["bio_conservation_metrics"]:
+    bio_metric_calc[bio_metric] = True
+for batch_metric in par["batch_correction_metrics"]:
+    batch_metric_calc[batch_metric] = True
+
+# Batch correction metrics
+logger.info(f">> Batch Correction Metrics: {par['batch_correction_metrics']}")
+# Dictionary with results of calculated metrics
+batch_metrics = {}
+
+# batch_metrics = {}
+if batch_metric_calc["asw_batch"]:
+    logger.info("Calculating ASW score (batches)")
+    asw_batch = scib.metrics.silhouette_batch(
+        adata_t,
+        batch_key=par["obs_batch_label"],
+        label_key=par["obs_cell_label"],
+        embed=par["obsm_embeddings"],
+        metric="euclidean",
+        return_all=False,
+        verbose=False,
+        )
+    batch_metrics["asw_batch"] = asw_batch
+else:
+    logger.info("Skipping ASW score (batches) calculation")
+    batch_metrics["asw_batch"] = np.nan
+    
+if batch_metric_calc["pcr"]:
+    logger.info("Calculating PC regression")
+    pcr_score = scib.metrics.pcr_comparison(
+        adata_t,
+        adata_t,
+        embed=par["obsm_embeddings"],
+        covariate=par["obs_batch_label"],
+        verbose=False
+        )
+    batch_metrics["pcr"] = pcr_score
+else:
+    logger.info("Skipping PC Regression calculation")
+    batch_metrics["pcr"] = np.nan
+
+if batch_metric_calc["graph_connectivity"]:
+    logger.info("Calculating graph connectivity")
+    graph_conn_score = scib.metrics.graph_connectivity(
+        adata_t,
+        label_key=par["obs_cell_label"]
+        )
+    batch_metrics["graph_connectivity"] = graph_conn_score
+else:
+    logger.info("Skipping graph connectivity calculation")
+    batch_metrics["graph_connectivity"] = np.nan
+
+if batch_metric_calc["ilisi_graph"]:
+    logger.info("Calculating graph iLISI")
+    graph_ilisi = scib.metrics.lisi.ilisi_graph(
+        adata_t,
+        batch_key=par["obs_batch_label"],
+        type_="knn",
+        use_rep=par["obsm_embeddings"]
+        )
+    batch_metrics["ilisi_graph"] = graph_ilisi
+else:
+    logger.info("Skipping graph iLISI calculation")
+    batch_metrics["ilisi_graph"] = np.nan
+    
+if batch_metric_calc["kbet"]:
+    logger.info("Calculating kBET")
+    kbet_score = scib.metrics.kBET(
+        adata_t,
+        batch_key=par["obs_batch_label"],
+        label_key=par["obs_cell_label"],
+        type_="knn",
+        embed=par["obsm_embeddings"],
+        verbose=True
+        )
+    batch_metrics["kbet"] = kbet_score
+else:
+    logger.info("Skipping kBET calculation")
+    batch_metrics["kbet"] = np.nan
+    
+# Bio conservation metrics
+logger.info(f">>Bio Conservation Metrics: {par['bio_conservation_metrics']}")
+
+# Dictionary to store results of bio conservation metrics 
+bio_metrics = {}
+
+if bio_metric_calc["nmi"]:
+    logger.info("Calculating NMI score")
+    nmi_score = scib.metrics.nmi(
+            adata_t,
+            cluster_key=par["obs_cluster"],
+            label_key=par["obs_cell_label"]
+        )
+    bio_metrics["nmi"] = nmi_score
+else:
+    logger.info("Skipping NMI calculation")
+    bio_metrics["nmi"] = np.nan
+    
+if bio_metric_calc["ari"]:
+    logger.info("Calculating ARI score")
+    ari_score = scib.metrics.ari(
+        adata_t,
+        cluster_key=par["obs_cluster"],
+        label_key=par["obs_cell_label"]
+        )
+    bio_metrics["ari"] = ari_score
+else:
+    logger.info("Skipping ARI calculation")
+    bio_metrics["ari"] = np.nan
+    
+if bio_metric_calc["asw_label"]:
+    logger.info("Calculating ASW score (cell types)")
+    asw_label = scib.metrics.silhouette(
+        adata_t,
+        label_key=par["obs_cell_label"],
+        embed=par["obsm_embeddings"]
+        )
+    bio_metrics["asw_label"] = asw_label
+else:
+    logger.info("Skipping ASW score (cell types) calculation")
+    bio_metrics["asw_label"] = np.nan
+    
+if bio_metric_calc["isolated_label_f1"]:
+    logger.info("Calculating isolated label F1")
+    il_score_f1 = scib.metrics.isolated_labels(
+        adata_t,
+        label_key=par["obs_cell_label"],
+        batch_key=par["obs_batch_label"],
+        embed=par["obsm_embeddings"],
+        cluster=True
+        )
+    bio_metrics["isolated_label_f1"] = il_score_f1
+else:
+    logger.info("Skipping isolated label F1 calculation")
+    bio_metrics["isolated_label_f1"] = np.nan
+
+if bio_metric_calc["isolated_label_asw"]:
+    logger.info("Calculating isolated label silhouette")
+    il_score_asw = scib.metrics.isolated_labels(
+        adata_t,
+        label_key=par["obs_cell_label"],
+        batch_key=par["obs_batch_label"],
+        embed=par["obsm_embeddings"],
+        cluster=False
+        )
+    bio_metrics["isolated_label_asw"] = il_score_asw
+else:
+    logger.info("Skipping isolated label ASW calculation")
+    bio_metrics["isolated_label_asw"] = np.nan
+
+if bio_metric_calc["clisi_graph"]:
+    logger.info("Calculating graph cLISI")
+    graph_clisi = scib.metrics.clisi_graph(
+        adata_t,
+        label_key=par["obs_cell_label"],
+        type_="knn",
+        use_rep=par["obsm_embeddings"]
+    )
+    bio_metrics["clisi_graph"] = graph_clisi
+else:
+    logger.info("Skipping isolated graph cLISI calculation")
+    bio_metrics["clisi_graph"] = np.nan
+    
+logger.info(">> Aggregate Metrics")
+logger.info(f"Calculating Bio Conservation Score based on {par['bio_conservation_metrics']} ")
+# Calculate the mean of the bio conservation metrics ignoring the nan values
+avg_bio = np.nanmean(list(bio_metrics.values()))
+
+logger.info(f"Calculating Batch Correction Score based on {par['batch_correction_metrics']}")
+# Calculate the mean of the bio conservation metrics ignoring the nan values
+avg_batch = np.nanmean(list(batch_metrics.values()))
+
+logger.info("Calculating Overall Score")
+# Weighted mean of the bio conservation and batch correction scores 
+# See https://doi.org/10.1038/s41592-021-01336-8
+overall_score = (0.4 * avg_batch) + (0.6 * avg_bio)
+
+
+logger.info("Writing output data")
+adata.uns["bio_conservation_metrics"] = bio_metrics
+adata.uns["batch_correction_metrics"] = batch_metrics
+adata.uns["bio_conservation_score"] = avg_bio
+adata.uns["batch_correction_score"] = avg_batch
+adata.uns["overall_integration_score"] = overall_score
+
+mdata.mod[par["modality"]] = adata
+mdata.write(par["output"], compression=par["output_compression"])
diff --git a/src/qc/integration_report/config.vsh.yaml b/src/qc/integration_report/config.vsh.yaml
new file mode 100644
index 00000000000..7b1285e5289
--- /dev/null
+++ b/src/qc/integration_report/config.vsh.yaml
@@ -0,0 +1,122 @@
+functionality:
+  name: integration_report
+  namespace: "qc"
+  description: |
+    Generates a .md file containing an overview of integration metrics (calculated in qc/integration_metrics) and umap visualizations.
+      
+  authors:
+    - __merge__: /src/authors/dorien_roosen.yaml
+      roles: [ author ]
+  argument_groups:
+    - name: Inputs
+      arguments:
+        - name: "--input"
+          type: file
+          description: Input h5mu file
+          direction: input
+          required: true
+          example: input.h5mu
+        - name: "--modality"
+          type: string
+          default: "rna"
+        - name: "--var_gene_names"
+          type: string
+          required: false
+          description: |
+            The name of the adata var column containing gene names. When no gene_name_layer is provided, the var index will be used.
+        - name: "--obs_batch_label"
+          type: string
+          example: "sample"
+          required: true
+          description: |
+            The name of the adata obs column containing the batch labels.
+        - name: "--obs_cell_label"
+          type: string
+          example: "cell_type"
+          required: true
+          description: |
+            The name of the adata obs column containing the cell type labels.
+        - name: "--uns_neighbors"
+          type: string
+          example: "neighbors"
+          required: true
+          description:
+            The name of the adata uns object containing the neighbors information.
+        - name: "--obsm_umap"
+          type: string
+          example: "X_scGPT_umap"
+          required: true
+          description: "The obsm slot containing UMAP embeddings."
+
+    - name: Outputs
+      arguments:
+        - name: "--output"
+          type: file
+          required: true
+          description: Name of the integration qc output pdf report.
+          direction: output
+          example: output.pdf
+        - name: "--output_raw"
+          type: boolean_true
+          description: |
+            If provided, the raw data (unrendered report (md), figures (png) and metrics (json)) will be published.
+        - name: "--output_umap_label_fig"
+          type: file
+          direction: output
+          default: umap_label.png
+          must_exist: False
+          description: |
+            Name of the UMAP label figure (png). Will only be saved if --output_raw is set to true.
+        - name: "--output_umap_batch_fig"
+          type: file
+          direction: output
+          must_exist: False
+          default: umap_batch.png
+          description: |
+            Name of the UMAP batch figure (png). Will only be saved if --output_raw is set to true.
+        - name: "--output_md_report"
+          type: file
+          direction: output
+          default: report.qmd
+          must_exist: False
+          description: |
+            Name of the unrendered report file (qmd). Will only be saved if --output_raw is set to true.
+        - name: "--output_metrics"
+          type: file
+          direction: output
+          must_exist: False
+          default: metrics.json
+          description: |
+            Name of the json file containing integration metrics (json). Will only be saved if --output_raw is set to true.       
+
+  resources:
+    - type: python_script
+      path: script.py
+    - path: report_template.md
+   
+platforms:
+  - type: docker
+    image: python:3.11
+    setup:
+      - type: apt
+        packages: 
+          - procps
+          - libhdf5-dev
+          - gfortran
+          - cmake
+          - libopenblas-dev
+      - type: python
+        __merge__: [ /src/base/requirements/anndata_mudata.yaml, /src/base/requirements/scanpy.yaml ]
+      - type: docker
+        run: |
+          wget https://github.com/quarto-dev/quarto-cli/releases/download/v1.4.549/quarto-1.4.549-linux-amd64.deb -O /tmp/quarto.deb && \
+          dpkg -i /tmp/quarto.deb && \
+          rm /tmp/quarto.deb && \
+          quarto install tinytex
+
+    test_setup:
+      - type: python
+        __merge__: [ /src/base/requirements/viashpy.yaml, .]
+  - type: nextflow
+    directives:
+      label: [singlecpu, lowmem]
\ No newline at end of file
diff --git a/src/qc/integration_report/report_template.md b/src/qc/integration_report/report_template.md
new file mode 100644
index 00000000000..43abeff1b17
--- /dev/null
+++ b/src/qc/integration_report/report_template.md
@@ -0,0 +1,49 @@
+---
+title: "Integration QC report"
+format: pdf
+tbl-colwidths: [70,20]
+---
+
+## Overview of integration metrics and scores
+
+The overall integration score is **{overall_integration}**. The integration score is a 40/60 weighted average of the batch correction score ({batch_correction}, table 1) and the biological conservation score ({bio_conservation}, table 2).
+
+
+::: {{layout-ncol=2}}
+
+| metric  | value  |
+|--------|--------|
+| NMI  | {nmi}   |
+| ARI   | {ari}   |
+| ASW (label) | {asw_label}   |
+| Isolated label (f1) | {isolated_label_f1}   |
+| Isolated label (ASW) | {isolated_label_asw}   |
+| cLISI   | {clisi_graph}   |
+| **biological conservation score** | **{bio_conservation}**   |
+
+: Biological conservation {{.striped}}
+
+| metric  | value  |
+|--------|--------|
+| ASW (batch)  | {asw_batch}   |
+| PCR   | {pcr}   |
+| Graph connectivity | {graph_connectivity}   |
+| iLISI | {ilisi_graph}   |
+| kBET | {kbet}   |
+| **batch correction score** | **{batch_correction}**   |
+
+: Batch correction {{.striped}}
+:::
+
+The biological conservation metrics consist of NMI (normalized mutual information), ARI (adjusted rand index), ASW (average silhouette width) label, isolated label (f1 and ASW) and graph cLISI (cell-type local inverse Simpson's index) metrics. The batch correction metrics consist of ASW, PCR (principal component regression), graph connectivity, iLISI (integration LISI) and kBET (k-nearest-neighbor batch effect test) metrics.
+The biological conservation and batch correction scores are the means of their individual metrics.
+
+All score and metrics calculations are based on the scib (single cell integration benchmark) library (https://doi.org/10.1038/s41592-021-01336-8). 
+
+## Visualizations of the integration embeddings
+
+![](umap_batch.png){{fig-align="center" width=70%}}
+
+![](umap_label.png){{fig-align="center" width=70%}}
+
+The integration embedding figures display the UMAP (uniform manifold approximation and projection) visualizations of the integrated data, colored by batch annotation or cell identity.  
\ No newline at end of file
diff --git a/src/qc/integration_report/script.py b/src/qc/integration_report/script.py
new file mode 100644
index 00000000000..2682ae49698
--- /dev/null
+++ b/src/qc/integration_report/script.py
@@ -0,0 +1,165 @@
+import scanpy as sc
+import mudata as mu
+import os
+import json
+import shutil
+import subprocess
+import tempfile
+from pathlib import Path
+
+
+## VIASH START
+par = {
+    "input": "resources_test/scgpt/test_resources/Kim2020_Lung_integrated_leiden_qc.h5mu",
+    "modality": "rna",
+    "var_gene_names": None,
+    "uns_neighbors": "scGPT_integration_neighbors",
+    "obsm_umap": "X_scGPT_umap",
+    "obs_batch_label": "sample",
+    "obs_cell_label": "cell_type",
+    "output": "test_report.pdf",
+    "output_raw": True,
+    "output_umap_label_fig": "test_umap_label.png",
+    "output_umap_batch_fig": "test_umap_batch.png",
+    "output_md_report": "test_report.qmd",
+    "output_metrics": "test_metrics.json"
+    }
+
+meta = {
+    "resources_dir": "src/qc/integration_report",
+    "functionality_name": "integration_report",
+    "temp_dir": "tmp"
+}
+
+## VIASH END
+
+# START TEMPORARY WORKAROUND setup_logger
+# reason: resources aren't available when using Nextflow fusion
+# from setup_logger import setup_logger
+def setup_logger():
+    import logging
+    from sys import stdout
+
+    logger = logging.getLogger()
+    logger.setLevel(logging.INFO)
+    console_handler = logging.StreamHandler(stdout)
+    logFormatter = logging.Formatter("%(asctime)s %(levelname)-8s %(message)s")
+    console_handler.setFormatter(logFormatter)
+    logger.addHandler(console_handler)
+
+    return logger
+# END TEMPORARY WORKAROUND setup_logger
+logger = setup_logger()
+
+logger.info("Reading in data")
+# Read in data
+mdata = mu.read(par["input"])
+input_adata = mdata.mod[par["modality"]]
+adata = input_adata.copy()
+
+# Ensure all batch labels are str
+adata.obs[par["obs_batch_label"]] = adata.obs[par["obs_batch_label"]].astype(str)
+
+# Generate vizualizations
+
+logger.info("Generating UMAP visualizations")
+fig_cell_type_clusters = sc.pl.embedding(
+    adata,
+    basis=par["obsm_umap"],
+    gene_symbols=par["var_gene_names"],
+    neighbors_key=par["uns_neighbors"],
+    color=par["obs_cell_label"],
+    title="UMAP visualization (label)",
+    frameon=False,
+    return_fig=True,
+    show=False,
+)
+
+fig_batch_clusters = sc.pl.embedding(
+    adata,
+    basis=par["obsm_umap"],
+    gene_symbols=par["var_gene_names"],
+    neighbors_key=par["uns_neighbors"],
+    color=par["obs_batch_label"],
+    title="UMAP visualization (batch)",
+    frameon=False,
+    return_fig=True,
+    show=False,
+)
+
+# Generate metrics and report
+
+# Open template
+with open(meta["resources_dir"] + '/report_template.md', 'r') as file:
+    template = file.read()
+
+# Context manager to generate temporary directory to save intermediary files
+with tempfile.TemporaryDirectory(
+        prefix=f"{meta['functionality_name']}-",
+        dir=meta["temp_dir"],
+        ignore_cleanup_errors=True) as temp_dir:
+
+    temp_dir = Path(temp_dir)
+    temp_dir.mkdir(parents=True, exist_ok=True)
+
+    # Directories for intermediary files
+    report_md = f"{temp_dir}/report.qmd"
+    umap_label_fig = f"{temp_dir}/umap_label.png"
+    umap_batch_fig = f"{temp_dir}/umap_batch.png"
+
+    # Save figures
+    fig_cell_type_clusters.savefig(umap_label_fig, dpi=300, bbox_inches='tight')
+    fig_batch_clusters.savefig(umap_batch_fig, dpi=300, bbox_inches='tight')
+
+    # Fetch variables required for report from the adata object
+    logger.info("Fetching integration metrics")
+    variables = {
+        "overall_integration": round(adata.uns["overall_integration_score"], 2),
+        "bio_conservation": round(adata.uns["bio_conservation_score"], 2),
+        "batch_correction": round(adata.uns["batch_correction_score"], 2),
+        "umap_batch": os.path.basename(umap_batch_fig),
+        "umap_label": os.path.basename(umap_label_fig)
+    }
+
+    # Round all variables, replace nan's with "-"
+    for k, v in adata.uns["bio_conservation_metrics"].items():
+        # Check if value is NaN and add to variables dict
+        variables[k] = round(v, 2) if v == v else "-"
+
+    for k, v in adata.uns["batch_correction_metrics"].items():
+        # Check if value is NaN and add to variables dict
+         variables[k] = round(v, 2) if v == v else "-"
+
+    logger.info("Generating report")
+    # Fill report template with variables
+    markdown_content = template.format(**variables)
+
+    # Save report
+    with open(report_md, 'w') as f:
+        f.write(markdown_content)
+
+    # PDF rendering
+    logger.info("Rendering report to pdf")
+    subprocess.run(['quarto', 'render', report_md, '--to', 'pdf'])
+
+    # Move report to output
+    logger.info("Publishing of pdf report")
+    shutil.move(f"{temp_dir}/report.pdf", par["output"])
+
+    # Save raw data
+    if not par["output_raw"]:
+        logger.info("Skipping publishing of raw output data because --output_raw was not provided.")
+    else:
+        logger.info("Publishing of raw output data")
+        shutil.move(umap_label_fig, par["output_umap_label_fig"])
+        shutil.move(umap_batch_fig, par["output_umap_batch_fig"])
+        shutil.move(report_md, par["output_md_report"])
+
+        # Remove figures from variable dict before saving as json
+        del variables["umap_batch"]
+        del variables["umap_label"]
+
+        metrics = {k: (str(v) if v == v else "-") for k, v in variables.items()}
+
+        with open(par["output_metrics"], 'w') as f:
+            json.dump(metrics, f)
diff --git a/src/workflows/qc/integration_qc/config.vsh.yaml b/src/workflows/qc/integration_qc/config.vsh.yaml
new file mode 100644
index 00000000000..c5d375484c8
--- /dev/null
+++ b/src/workflows/qc/integration_qc/config.vsh.yaml
@@ -0,0 +1,152 @@
+functionality:
+  name: integration_qc
+  namespace: "workflows/qc"
+  description: |
+    Workflow to add integration qc metrics to a MuData and generate an integration qc output report.
+      
+  authors:
+    - __merge__: /src/authors/dorien_roosen.yaml
+      roles: [ author, maintainer ]
+  argument_groups:
+    - name: Inputs
+      arguments:
+        - name: "--input"
+          type: file
+          description: Input h5mu file
+          direction: input
+          required: true
+          example: input.h5mu
+        - name: "--modality"
+          type: string
+          default: "rna"
+        - name: "--var_gene_names"
+          type: string
+          required: false
+          description: |
+            The name of the adata var column containing gene names. When no gene_name_layer is provided, the var index will be used.
+        - name: "--bio_conservation_metrics"
+          type: string
+          multiple: true
+          multiple_sep: ";"
+          choices: 
+            - nmi
+            - ari
+            - asw_label
+            - isolated_label_f1
+            - isolated_label_asw
+            - clisi_graph
+          default: nmi;ari;asw_label
+          description: |
+            The metrics to be calculated to assess biological conservation. 
+            The provided metrics will be aggregated into a biological conservation score.
+        - name: "--batch_correction_metrics"
+          type: string
+          multiple: true
+          multiple_sep: ";"
+          choices:
+            - asw_batch
+            - pcr
+            - graph_connectivity
+            - ilisi_graph
+            - kbet
+          default: asw_batch;pcr;graph_connectivity
+          description: |
+            The metrics to be calculated for the batch correction. 
+            The provided metrics will be aggregated into a batch correction score.
+            
+    - name: Input annotations
+      arguments:
+        - name: "--obsm_embeddings"
+          type: string
+          required: true
+          example: "X_scGPT"
+          description: |
+            The name of the adata.obsm array containing scGPT cell embeddings.
+        - name: "--obs_batch_label"
+          type: string
+          example: "sample"
+          required: true
+          description: |
+            The name of the adata obs column containing the batch labels.
+        - name: "--obs_cell_label"
+          type: string
+          example: "cell_type"
+          required: true
+          description: |
+            The name of the adata obs column containing the cell type labels.
+        - name: "--obs_cluster"
+          type: string
+          example: "cluster"
+          required: true
+          description: |
+            The name of the adata obs column containing the cluster labels.
+        - name: "--obsp_neighbor_connectivities"
+          type: string
+          example: "connectivities"
+          required: true
+          description: |
+            The name of the adata obsp object containing the neighbor connectivities.
+        - name: "--uns_neighbors"
+          type: string
+          example: "neighbors"
+          required: true
+          description:
+            The name of the adata uns object containing the neighbors information.
+        - name: "--obsm_umap"
+          type: string
+          example: "X_scGPT_umap"
+          required: true
+          description: "The obsm slot containing UMAP embeddings."
+
+    - name: Outputs
+      arguments:
+        - name: "--output"
+          type: file
+          required: true
+          description: Name of the integration qc output pdf report.
+          direction: output
+          example: output.pdf
+        - name: "--output_raw"
+          type: boolean_true
+          description: |
+            If provided, the raw data (unrendered report (md), figures (png) and metrics (json)) will be published.
+        - name: "--output_md_report"
+          type: file
+          direction: output
+          default: report.qmd
+          must_exist: False
+          description: |
+            Name of the unrendered report file (qmd). Will only be saved if --output_raw is set to true.
+        - name: "--output_umap_label_fig"
+          type: file
+          direction: output
+          default: umap_label.png
+          must_exist: False
+          description: |
+            Name of the UMAP label figure (png). Will only be saved if --output_raw is set to true.
+        - name: "--output_umap_batch_fig"
+          type: file
+          direction: output
+          must_exist: False
+          default: umap_batch.png
+          description: |
+            Name of the UMAP batch figure (png). Will only be saved if --output_raw is set to true.
+        - name: "--output_metrics"
+          type: file
+          direction: output
+          must_exist: False
+          default: metrics.json
+          description: |
+            Name of the json file containing integration metrics (json). Will only be saved if --output_raw is set to true.       
+
+
+  dependencies:
+    - name: qc/integration_metrics
+    - name: qc/integration_report
+  resources:
+    - type: nextflow_script
+      path: main.nf
+      entrypoint: run_wf
+   
+platforms:
+  - type: nextflow
diff --git a/src/workflows/qc/integration_qc/main.nf b/src/workflows/qc/integration_qc/main.nf
new file mode 100644
index 00000000000..146969c5d81
--- /dev/null
+++ b/src/workflows/qc/integration_qc/main.nf
@@ -0,0 +1,46 @@
+workflow run_wf {
+  take:
+  input_ch
+
+  main:
+  output_ch = input_ch
+    // Calculate integration qc metrics and add them to the MuData file
+    | integration_metrics.run(
+      fromState: [
+        "input": "input",
+        "modality": "modality",
+        "obsm_output": "obsm_output",
+        "bio_conservation_metrics": "bio_conservation_metrics",
+        "batch_correction_metrics": "batch_correction_metrics",
+        "obsm_embeddings": "obsm_embeddings",
+        "obs_batch_label": "obs_batch_label",
+        "obs_cell_label": "obs_cell_label",
+        "obs_cluster": "obs_cluster",
+        "uns_neighbors": "uns_neighbors",
+        "obsp_neighbor_connectivities": "obsp_neighbor_connectivities",
+      ],
+      toState: [
+        "input": "output"
+      ]
+    )
+    
+    // Generate visualizations and a report based on the metrics
+    | integration_report.run(
+      fromState: [
+        "input": "input",
+        "modality": "modality",
+        "var_gene_names": "var_gene_names",
+        "obs_batch_label": "obs_batch_label",
+        "obs_cell_label": "obs_cell_label",
+        "uns_neighbors": "uns_neighbors",
+        "obsm_umap": "obsm_umap",
+        "output_raw": "output_raw"
+      ],
+      toState: { id, output, state ->
+        output
+      }
+    )
+
+  emit:
+  output_ch
+}
\ No newline at end of file
diff --git a/src/workflows/qc/integration_qc/nextflow.config b/src/workflows/qc/integration_qc/nextflow.config
new file mode 100644
index 00000000000..8108bc25e84
--- /dev/null
+++ b/src/workflows/qc/integration_qc/nextflow.config
@@ -0,0 +1,10 @@
+manifest {
+  nextflowVersion = '!>=20.12.1-edge'
+}
+
+params {
+  rootDir = java.nio.file.Paths.get("$projectDir/../../../../").toAbsolutePath().normalize().toString()
+}
+
+// include common settings
+includeConfig("${params.rootDir}/src/workflows/utils/labels.config")
\ No newline at end of file