PaSTa is a nextflow-based end-to-end image analysis pipeline for decoding image-based spatial transcriptomics data. It performs imaging cycle registration, cell segmentation and transcripts peak decoding. It is currently supports analysis of three types of ST technology:

• in-situ sequencing-like encoding
• MERFISH-like encoding
• RNAScope-like labelling

Prerequisites: 1. Nextflow. Installation guide: https://www.nextflow.io/docs/latest/getstarted.html 2. Docker or Singularity. Installation guide: https://docs.docker.com/get-docker/ or https://sylabs.io/guides/3.7/user-guide/quick_start.html

Demo run with GitPod

Check this HackMD from I2K2024 workshop: https://hackmd.io/w4DeWEDxRlKwIPTDCc77XA

Basic run

1. Clone the repository git clone https://github.com/cellgeni/Image-ST.git

2. Prepare the run.config file * ``` process { withName: CELLPOSE { ext.args = "--channels [0,0]" storeDir = "./output/naivecellposesegmentation/" }

   withName: POSTCODE {
           memory = {20.Gb * task.attempt}
           storeDir = "./output/PoSTcode_decoding_output"
   }
   
   withName: TO_SPATIALDATA {
           memory = {20.Gb * task.attempt}
           ext.args = "--feature_col 'Name' --expansion_in_pixels 30 --save_label_img False"
   }
   
   withName: MERGE_OUTLINES {
           storeDir = "./output/merged_cellpose_segmentation/"
   }
   
   withName: BIOINFOTONGLI_MICROALIGNER {
           memory = {50.Gb * task.attempt}
           storeDir = "./output/registered_stacks"
   }
   
   withName: BIOINFOTONGLI_TILEDSPOTIFLOW {
           memory = {30.Gb * task.attempt}
           storeDir = "./output/spotiflow_peaks/"
   }
   
   withName: BIOINFOTONGLI_MERGEPEAKS {
           memory = {50.Gb * task.attempt}
           storeDir = "./output/spotiflow_peaks/"
   }
   
   withName: BIOINFOTONGLI_CONCATENATEWKTS {
           memory = {50.Gb * task.attempt}
           storeDir = "./output/spotiflow_peaks/"
   }
   
   withName: EXTRACT_PEAK_PROFILE {
           memory = {50.Gb * task.attempt}
           storeDir = "./output/peak_profiles/"
   }
   

   } ```

3. Prepare the parameters file (e.g. iss.yaml) ``` images:

   • ['id': "test", [ "cycle1.ome.tiff", "cycle2.ome.tiff", "cycle3.ome.tiff", "cycle4.ome.tiff", "cycle5.ome.tiff", "cycle6.ome.tiff", ] ] celldiameters: [30] chstocallpeaks: [1,2] // channels to call peaks, can be multiple codebook:
   • ['id': "test", "./codebook.csv", "./dummy.txt"] // has to match the meta in images variable segmentation_method: "CELLPOSE" // or DEEPCELL or STARDIST or INSTANSEG

outdir: "./output" 4. Run the pipeline nextflow run ./Image-ST/main.nf -profile lsf,singularity -c run.config -params-file iss.yaml -entry RUNDECODING -resume ``` 5. Check the output in the specified storeDir.

Spin up Napari with napari-spatialdata plugin installed (https://spatialdata.scverse.org/projects/napari/en/latest/notebooks/spatialdata.html)

Then use the following command to visualize the output ``` from napari_spatialdata import Interactive import spatialdata as spd

data = spd.read_zarr([path-to-.sdata-folder]) Interactive(data) ```

*: You may leave the process block empty if you want to use the default parameters.

FAQ

1. My HOME dir is full when running Singularity image conversion on HPC.

A quick solution is to manually specify singularity dir by setting:

singularity cache clean export SINGULARITY_CACHEDIR=./singularity_image_dir export NXF_SINGULARITY_CACHEDIR=./singularity_image_dir

1. How do I modify parameters to specific process/step?

By following nf-core standard, it is possible to add any parameters to the main script using ext.args=”--[key] [value]” in the run.config file.

An example is

withName: POSTCODE { ext.args = "--codebooktargercol L-probe --codebookcodecol code " }

1. Cannot download pretrained model for the deep-learning tools (Spotiflow/CellPose)

Exception: URL fetch failure on https://drive.switch.ch/index.php/s/6AoTEgpIAeQMRvX/download: None -- [Errno -3] Temporary failure in name resolution Or CellPose urllib.error.URLError:

Mostly likely you've reached max download (?), wait a bit and try later OR manually download those models and update the configuration file.