NextFlow 101

To use

1. Have mamba and git installed

2. Clone this repository on your local machine, open a Terminal window, and move to the repository's folder:

   cd /my/file/path/to/nextflow101/
   

3. Create conda environment from yaml file:

   mamba env create -f nextflow101_env.yml
   

4. Activate environment:

   mamba activate nextflow101
   

5. Download the BBBC010 dataset, more specifically:

• The original images provided as BBBC010_v2_images.zip (70 MB)
• The binary segmentation masks for each object provided as BBBC010_v1_foreground_eachworm.zip (2.7 MB)

To understand what you will do in the exercises, it is advisable to spend a couple of minutes taking the time to read the description of what the BBBC010 is!

6. Place the two .zip in the data/raw subfolder, and unzip them into two sub directories with names matching the .zip file name (BBBC010_v2_images, 200 files, and BBBC010_v1_foreground_eachworm, 1407 files).

Depending on your OS and setup, these folders will be created automatically when unzipping. If the unzipping operation does NOT create new subfolders and simply populates data/raw with individual files, you must manually create one subfolder BBBC010_v2_images and move the unzipped content of BBBC010_v2_images.zip into it, and then manually create a second subfolder BBBC010_v1_foreground_eachworm and move the unzipped content of BBBC010_v1_foreground_eachworm.zip into it.

7. Move to the exercises subfolder:

   cd exercises/
   

8. Move to the specific exercise subfolder of your choice:

   cd N-my-favourite-exercise/
   

9. Read the corresponding README.md and complete the exercise

10. If you get stuck, solutions are provided in the solutions subfolder.

Troubleshooting

If, at step 3 above, the nextflow101_env.yml fails to install for whichever reason, try to create it manually with the following:

mamba create -n nextflow101-manual python=3.10
source activate nextflow101-manual     

mamba install nextflow -c bioconda -c conda-forge
mamba install numpy
mamba install scikit-image
mamba install scikit-learn
mamba install pandas
mamba install matplotlib
mamba install seaborn

Then close your terminal window, open a new one, and continue at point 3 of the "to use" instructions above.

If, at step 4 above, the mamba activate commands returns an error, try the following:

source activate nextflow101

To cite

If you use or refer to this tutorial, please acknowledge it as follows:

Uhlmann, V. (2025) NextFlow 101 Tutorial. github.com/uhlmanngroup/nextflow101

Further resources

• NextFlow reference documentation, https://www.nextflow.io/docs/latest/reference/.
• GloBIAS Seminar Series: NextFlow for BioImage Analysis by Christian Tischer, Tong Li, Miguel Ibarra and Tim-Oliver Buchholz, available on YouTube.
• Minimal Nextflow OME-Zarr workflow from Tong Li, available on GitHub.

Acknowledgements

Ignacio Arganda-Carreras (University of the Basque Country, Spain), Anna Klemm (Scilifelab & Uppsala University, Sweden), Perrine Paul-Gilloteaux (University of Nantes, France), and Christian Tischer (EMBL Heidelberg, Germany) are to be thanked for prompting the creation of this tutorial in the context of the 2025 EMBO Practical Course on Advanced methods in bioimage analysis.