nf-core · CaroAMN · Jan 23, 2026 · Jan 20, 2026 · Jan 20, 2026 · Jan 21, 2026
diff --git a/README.md b/README.md
@@ -21,53 +21,33 @@
 
 ## Introduction
 
-**nf-core/lsmquant** is a bioinformatics pipeline that performs preprocessing and analysis of light-sheet microscopy images of tissue cleared samples. The pipeline takes 2D single-channel 16-bit `.tif` images as input. The preprocessing consists of intesity adjustment, channel alignment, and tile stitching to reconstruct the 3D image. For mousebrain samples it offers a registration to the Allen Mouse Brain Reference Atlas for precise region annotation. Cell nuclei quantification is perfomed on the nuclear channel by a 3D-Unet.
+**nf-core/lsmquant** is a bioinformatics pipeline that performs preprocessing and analysis of light-sheet microscopy images of tissue cleared samples. The pipeline takes raw images from a directory or a zip archive as input. The images need to be in a 2D single-channel 16-bit `tif`format.
 
 <div style="text-align: center;">
 <img src="docs/images/lsmquant-metromap.svg" alt="lasmquant metromap">
 </div>
 
-## Basic workflow
-
-**Preprocessing**
-
-1. Intensity Adjustment
-2. Channel Alignment
-3. Iterative Stitching
-
-**ARA Registration**
-
-4. ARA Registration subworkflow (optional)
-5. Cell Nuclei Quantification
-
-**Full**
-
-1. Preprocessing
-2. Nuclei quantification
-
 ## Pipeline Summary
 
-The pipeline consists of two major workflows `preprocessing` and the `full` workflow. The `ara-regsitration` is an optional subworkflow that works only for whole mouse brain samples.
+The pipeline consists of 3 major components: Preprocessing, Cell-Nuclei quantification, and Allen Reference Atlas registration. A detailed explanation on each method can be found in the [Methods description](./docs/usage.md) section.
 
-### Preprocessing
+**Preprocessing**
 
-Preprocessing is performed on raw 2D single-channel 16-bit `.tif` images produced by a light sheet microscope. Three individual steps are performed:
+This stage reconstructs the 3D image from raw light-sheet data. Here two different workflows can be chosen:
 
-- **Intensity adjustments** to correct for the Gaussian shape of the lightsheet and intensity differences between adjacent tiles
-- **Image channel alignment** using a 2D rigid approach or a nonlinear 3D approach using Elastix.
-- **Image tile stitching** via an iterative 2D stitching approach by calculating z displacements and xy translations using phase correlation and SIFT.
+1. `align_stitch` for multi-channel brain images: \
+   Performs intensity adjustment, channel alignment, and iterative tile stitching
 
-### Full
+2. `stitch` for single-channel images: \
+   Performs intensity adjustment and interactive tile stitching.
 
-Quantification of cell-nuclei is performed using a 3D-Unet. It is performed on the nuclear channel only, assuming that the corresponding image file names contain the pattern `C1`.
+**Allen Brain Atlas Registration (Optional)**
 
-### ARA Registration
+This workflow registers full brain images to the Allen Brain Reference Atlas. This is an optional workflow and can be chosen by setting the parameter: `ara_registartion`
 
-Optional registration to the Allen Reference Atlas (ARA) for functional brain region annotation can be perfomed before segmentation.
-This includes the following two steps:
+**Cell Nuclei Quantification**
 
-- Downsampling of the high resolution stitched images
-- Registration to the ARA
+Quantification of cell-nuclei is performed using a 3D-Unet and it is performed on the nuclear channel only. This is an optional workflow and can be chosen by setting the parameter:`nuclei_quantification`
 
 ## Usage
 
@@ -130,7 +110,7 @@ We thank the following people for their extensive assistance in the development
 [Mark Polster](https://github.com/mapo9)\
 [Susi Jo](https://github.com/SusiJo)\
 [Luis Kuhn Cuellar](https://github.com/luiskuhn)\
-[Daniel Straub](https://github.com/d4straub)
+[Daniel Straub](https://github.com/d4straub)\
 [Tatiana Woller](https://github.com/tatianawoller)\
 [Niklas Grote](https://github.com/HomoPolyethylen)\
 Jason Stein\

diff --git a/conf/test.config b/conf/test.config
@@ -28,5 +28,6 @@ params {
     config_profile_name        = 'Test profile'
     config_profile_description = 'Minimal test dataset to check pipeline function'
     input  = params.pipelines_testdata_base_path + '/test_data/samplesheets/sample_sheet.csv'
-    stage  = 'full'
+    stage  = 'align_stitch'
+    nuclei_quantification = true
 }
diff --git a/conf/test_full.config b/conf/test_full.config
@@ -21,5 +21,6 @@ params {
     config_profile_name        = 'Full test profile'
     config_profile_description = 'Full test dataset to check pipeline function'
     input  = params.pipelines_testdata_base_path + '/test_data/samplesheets/sample_sheet.csv'
-    stage  = 'full'
+    stage  = 'align_stitch'
+    nuclei_quantification = true
 }
diff --git a/modules/local/numorphstitch/main.nf b/modules/local/numorphstitch/main.nf
@@ -25,12 +25,20 @@ process NUMORPHSTITCH {
     script:
     def args = task.ext.args ?: ''
     def prefix = task.ext.prefix ?: "${meta.id}"
+    def alignment_table = alignment_table_mat.name ? alignment_table_mat : ''
+    def z_displacement_align = z_displacement_align_mat ? z_displacement_align_mat : ''
     """
 
     mkdir -p results/variables/
 
-    ln -sr ${alignment_table_mat} results/variables
-    ln -sr ${z_displacement_align_mat} results/variables
+    if [ -n "${alignment_table}" ]; then
+        ln -sr ${alignment_table} results/variables/
+    fi
+
+    if [ -n "${z_displacement_align}" ]; then
+        ln -sr ${z_displacement_align} results/variables
+    fi
+
     ln -sr ${thresholds_mat} results/variables
     ln -sr ${adj_params_mat} results/variables
     ln -sr ${path_table_mat} results/variables

diff --git a/nextflow.config b/nextflow.config
@@ -11,16 +11,17 @@ params {
 
     // Input options
     input                       = null
-    stage                       = 'preprocessing'
+    stage                       = 'align_stitch'
     ara_registration            = false
+    nuclei_quantification       = false
     model_file                  = 'https://zenodo.org/records/16893708/files/075_121_model.h5' // Path to the pre-trained model file
 
 
     // MultiQC options
-    multiqc_config             = null
-    multiqc_title              = null
-    multiqc_logo               = null
-    max_multiqc_email_size     = '25.MB'
+    multiqc_config              = null
+    multiqc_title               = null
+    multiqc_logo                = null
+    max_multiqc_email_size      = '25.MB'
     multiqc_methods_description = null
 
     // Boilerplate options
@@ -37,8 +38,8 @@ params {
     version                      = false
     pipelines_testdata_base_path = 'https://raw.githubusercontent.com/nf-core/test-datasets/lsmquant/'
     trace_report_suffix          = new java.util.Date().format( 'yyyy-MM-dd_HH-mm-ss')// Config options
-    config_profile_name        = null
-    config_profile_description = null
+    config_profile_name          = null
+    config_profile_description   = null
 
     custom_config_version      = 'master'
     custom_config_base         = "https://raw.githubusercontent.com/nf-core/configs/${params.custom_config_version}"

diff --git a/nextflow_schema.json b/nextflow_schema.json
@@ -29,7 +29,7 @@
                 "stage": {
                     "type": "string",
                     "description": "The stage of the pipeline to run.",
-                    "help_text": "The stage of the pipeline to run. The pipeline has multiple stages that can be run separately or the complete pipeline can be run. Stages are: `full`, `preprocess`",
+                    "help_text": "The stage of the pipeline to run. The pipeline has multiple stages that can be run separately or the complete pipeline can be run. Stages are: `stitch`, `align_stitch`",
                     "fa_icon": "fas fa-cogs"
                 },
                 "ara_registration": {
@@ -38,6 +38,12 @@
                     "help_text": "Performs Allen Reference Atlas registration of stitched images. This step is optional and can be skipped if the images are already registered.",
                     "fa_icon": "fas fa-file-image"
                 },
+                "nuclei_quantification": {
+                    "type": "boolean",
+                    "description": "Performs cell nuclei quantification using a pre-trained model.",
+                    "help_text": "Performs cell nuclei quantification using a pre-trained model. This step is optional and can be skipped if not needed.",
+                    "fa_icon": "fas fa-calculator"
+                },
                 "model_file": {
                     "type": "string",
                     "description": "Path to the pre-trained model file.",

diff --git a/ro-crate-metadata.json b/ro-crate-metadata.json
diff --git a/subworkflows/local/numorph_stitch/main.nf b/subworkflows/local/numorph_stitch/main.nf
@@ -0,0 +1,76 @@
+include { NUMORPHINTENSITY                     } from '../../../modules/local/numorphintensity/'
+include { NUMORPHSTITCH                        } from '../../../modules/local/numorphstitch/'
+include { MAT2JSON as MAT2JSON_INT             } from '../../../modules/local/mat2json/'
+include { MAT2JSON as MAT2JSON_STITCH          } from '../../../modules/local/mat2json/'
+include { softwareVersionsToYAML               } from '../../../subworkflows/nf-core/utils_nfcore_pipeline/'
+
+workflow NUMORPH_STITCH {
+
+    take:
+
+    samplesheet  // channel: [ val(meta), path(img_directory), path(parameter_file) ]
+
+
+    main:
+
+    ch_versions = Channel.empty()
+
+    sample_meta = samplesheet.map { meta, img_dir, params -> meta }
+
+    NUMORPHINTENSITY (samplesheet)
+    def intensity_out = NUMORPHINTENSITY.out
+    ch_versions = ch_versions.mix(intensity_out.versions)
+
+    // Create a tuple channel with all mat files and appropriate meta
+    sample_meta.combine(NUMORPHINTENSITY.out.adj_params_mat)
+    .mix(
+        sample_meta.combine(NUMORPHINTENSITY.out.path_table_mat),
+        sample_meta.combine(NUMORPHINTENSITY.out.thresholds_mat),
+        sample_meta.combine(NUMORPHINTENSITY.out.NM_variables)
+    )
+    .set { mat_files_int}
+
+    // empty channels for alignment outputs
+    empty_align_table_mat = samplesheet.map {[]}
+    empty_z_displacement_align_mat = samplesheet.map {[]}
+
+    NUMORPHSTITCH (
+        samplesheet,
+        empty_align_table_mat,
+        empty_z_displacement_align_mat,
+        intensity_out.path_table_mat,
+        intensity_out.thresholds_mat,
+        intensity_out.adj_params_mat,
+        intensity_out.NM_variables
+        )
+
+    def stitch_out = NUMORPHSTITCH.out
+    ch_versions = ch_versions.mix(stitch_out.versions)
+
+    stitch_out.variables
+        .flatten()
+        .filter { file -> file.toString().endsWith('.mat') }
+        .combine(sample_meta)
+        .map {file, meta -> tuple(meta, file) }
+        .set { mat_files_stitch }
+
+    MAT2JSON_INT (mat_files_int, "intensity" )
+    MAT2JSON_STITCH (mat_files_stitch, "stitch" )
+    ch_versions = ch_versions.mix(MAT2JSON_INT.out.versions)
+
+    // Collate and save software versions
+    //
+    softwareVersionsToYAML(ch_versions)
+        .collectFile(
+            storeDir: "${params.outdir}/pipeline_info",
+            name: 'nf_core_'  +  'lsmquant_software_'  + 'mqc_'  + 'versions.yml',
+            sort: true,
+            newLine: true
+        ).set { ch_collated_versions }
+
+    emit:
+    stitched                  = stitch_out.stitched                    // channel: [ path(stitched_dir) ]
+    intensity_thresholds      = intensity_out.thresholds_mat           // channel: [path(thresholds_mat) ]
+    NM_variables              = stitch_out.NM_variables                // channel: [path(NM_variables) ]
+    versions                  = ch_collated_versions
+}
diff --git a/subworkflows/local/numorph_stitch/meta.yml b/subworkflows/local/numorph_stitch/meta.yml
@@ -0,0 +1,47 @@
+# yaml-language-server: $schema=https://raw.githubusercontent.com/nf-core/modules/master/subworkflows/yaml-schema.json
+name: "numorph_stitch"
+description: perform preprocessing with only intensity adjustment and stitching of 2D single channel single tile TIFF images.
+keywords:
+  - intensity
+  - stitching
+  - tiff
+components:
+  - numorphintensity
+  - numorphstitch
+  - mat2json
+input:
+  - samplesheet:
+      type: tuple
+      description: |
+        The input channel containing the metadata, image directory and parameter file.
+        Structure: [ val(meta), path(img_directory), path(parameter_file)]
+      pattern: "*.{tif/tiff/csv}"
+output:
+  - stitched:
+      type: path
+      description: |
+        Channel containing path to stitched Tiff files
+        Structure: [ val(meta), path(stitched) ]
+      pattern: "*.tif/tiff"
+  - intensity_thresholds:
+      type: file
+      description: |
+        Channel containing intensity threshold (MAT) file
+        Structure:  path(thresholds_mat)
+      pattern: "*.mat"
+  - NM_variables:
+      type: file
+      description: |
+        Channel containing numorph processing parameter file (MAT)
+        Structure:  path(NM_variables.mat)
+      pattern: "*.mat"
+  - versions:
+      type: file
+      description: |
+        File containing software versions
+        Structure: [ path(versions.yml) ]
+      pattern: "versions.yml"
+authors:
+  - "@CaroAMN"
+maintainers:
+  - "@CaroAMN"
diff --git a/subworkflows/local/numorph_stitch/tests/main.nf.test b/subworkflows/local/numorph_stitch/tests/main.nf.test
@@ -0,0 +1,64 @@
+nextflow_workflow {
+
+    name "Test Subworkflow NUMORPH_STITCH"
+    script "../main.nf"
+    workflow "NUMORPH_STITCH"
+
+    tag "subworkflows"
+    tag "subworkflows_"
+    tag "subworkflows/numorph_stitch"
+    tag "numorph"
+    tag "numorph preprocessing"
+    tag "numorph intensity"
+    tag "numorph stitch"
+
+
+    test("Numorph intensity and stitch only") {
+
+        setup {
+            run ("UNZIP") {
+                script "../../../../modules/nf-core/unzip/main.nf"
+                process {
+                    """
+                    input[0] = Channel.fromList([
+                        tuple([ id:'TEST1'],
+                        file('https://zenodo.org/records/14916478/files/ctip2_topro.zip'))
+                    ])
+                """
+                }
+            }
+        }
+        when {
+            params {
+                outdir = "$outputDir"
+            }
+            workflow {
+                """
+                input[0] = UNZIP.out.unzipped_archive.map { meta, unzipped_archive ->
+                    tuple(
+                    meta,
+                    unzipped_archive,
+                    file(params.pipelines_testdata_base_path + '/test_data/parameterfiles/params_TEST1_lsmquant.csv'))
+                }
+                """
+            }
+        }
+
+        then {
+            def stable_name = getAllFilesFromDir(params.outdir, relative: true, includeDir: true, ignore: ['pipeline_info/*.{html,json,txt}'])
+            def stable_path = getAllFilesFromDir(params.outdir, ignoreFile: 'subworkflows/local/numorph_preprocessing/tests/.nftignore')
+            assert workflow.success
+            assertAll(
+                { assert snapshot(
+                    // Number of successful tasks
+                    workflow.trace.succeeded().size(),
+                    removeNextflowVersion("$outputDir/pipeline_info/nf_core_lsmquant_software_mqc_versions.yml"),
+                    // All stable path name, with a relative path
+                    stable_name.isEmpty() ? 'No stable paths' : stable_name,
+                    // All files with stable contents
+                    stable_path
+                ).match()}
+            )
+        }
+    }
+}