Introduction

nf-core/lsmquant is a bioinformatics pipeline that performs preprocessing and analysis of light-sheet microscopy images of tissue cleard samples. The pipeline takes 2D single-channel 16-bit .tif images as input. The preprocessing consists of intesity adjustment, channel alignemnt, and tile stitching to reconstruct the 3D image. For mousebrain samples it offers a regsitration to the Allen Mouse Brain Reference Atlas for precise region annotation. Analysis of images can include call quantification via segmentation by a 3D-Unet and celltype classification by SVMs.

Basic workflow

1. Intensity Adjustment
2. Channel Alignment
3. Iterative Stitching
4. Resampling (not added)
5. Allen Referece Atlas Registration (not added)

Pipeline Summary

The pipeline consists of three major stages, the preprocessingstage, the registrationstage, and the analysis stage.

Preprocessing

For raw 2D single-channel 16-bit .tif images produced by a light sheet microscope preprocessing can be performed to recostruct the 3D image in nifti (.nii) format for further analysis. The complete preprocessing workflow performs:

• intensity adjustemnt of the images
• image channel alignemnt for at least two different channels
• image tile stitching to recustruct the full image for each channel and z-slice

Registration

Currently only available for whole mouse brain samples, recostructed images in .niiformat can be registerd to the Allen Reference Atlas (ARA) for functional brain region annotation. The workflow performs:

• downsampling of the high resolution .niiimages
• registration to the ARA

Analysis

Analysis will include semantic segmentation of cell nuclei via 3D-Unet

Work in progress..

Usage

Note

If you are new to Nextflow and nf-core, please refer to this page on how to set-up Nextflow. Make sure to test your setup with -profile test before running the workflow on actual data.

To run the pipeline you need to provide a parameter sheet (.csv file) that needs to have this specific structure: Please get the basic tempalte file here ( include maybe link to template csv which can be found in the repo ?) parametersheet.csv

Please specify which step you want to run with --stage. The following are valide options:

• 'intensity'
• 'align'
• 'stitch'
• 'resample'
• 'register'
• 'process'

Now, you can run the pipeline using:

nextflow run nf-core/lsmquant \
   -profile <docker/singularity/.../institute> \
   --input <path/to/image/folder> \
   --outdir <OUTDIR> \
   --parameter_file <filepath> \
   --sample_name <samplename> \
   --stage <stage> 

Warning

Please provide pipeline parameters via the CLI or Nextflow -params-file option. Custom config files including those provided by the -c Nextflow option can be used to provide any configuration except for parameters; see docs.

For more details and further functionality, please refer to the usage documentation and the parameter documentation.

Pipeline output

To see the results of an example test run with a full size dataset refer to the results tab on the nf-core website pipeline page. For more details about the output files and reports, please refer to the output documentation.

Credits

nf-core/lsmquant was originally written by Carolin Schwitalla.

The pipeline is mainly based on the NuMorph (Nuclear-Based Morphometry) toolbox developed by Krupa et al., 2021.

NuMorph: Tools for cortical cellular phenotyping in tissue-cleared whole-brain images

Krupa O, Fragola G, Hadden-Ford E, Mory JT, Liu T, Humphrey Z, Rees BW, Krishnamurthy A, Snider WD, Zylka MJ, Wu G, Xing L, Stein JL.

Cell Rep. 2021 Oct 12, doi: 10.1016/j.celrep.2021.109802

We thank the following people for their extensive assistance in the development of this pipeline:

Contributions and Support

If you would like to contribute to this pipeline, please see the contributing guidelines.

For further information or help, don't hesitate to get in touch on the Slack #lsmquant channel (you can join with this invite).

Citations

An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md file.

You can cite the nf-core publication as follows:

The nf-core framework for community-curated bioinformatics pipelines.

Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.

Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.