Zarrify

Convert TIFF/TIFF Stacks, MRC, and N5 files to Zarr (v2) format with OME-NGFF 0.4 metadata.

Prerequisites

You must install Pixi to run this tool.

Install into local env

After you check out the repo, run Pixi to download dependencies and create the local environment:

pixi run dev-install

Usage

Step 1: Convert image to OME-Zarr format

To convert an OME-TIFF image with axes ZCYX:

pixi run zarrify --src=/path/to/input --dest=/path/to/output.zarr   --axes z c y x --units nanometer '' nanometer nanometer --zarr_chunks 64 3 128 128

Step 2: Add multiscale pyramid

To add multiscale pyramids to the above OME-Zarr:

pixi run zarr-multiscale --config=/path/to/config.yaml

Where config.yaml contains the parameters, e.g.:

src: "/path/to/output.zarr"
workers: 50
data_origin: "raw"
cluster: "lsf"
log_dir: "/path/to/logs/workers"
antialiasing: false
high_aspect_ratio: false
custom_scale_factors: 
  - [1, 1, 1, 1]
  - [1, 1, 2, 2]
  - [1, 1, 4, 4]
  - [1, 1, 8, 8]
  - [1, 2, 16, 16]
  - [1, 4, 32, 32]
  - [1, 8, 64, 64]
  - [1, 16, 128, 128]
  - [1, 32, 256, 256]
  - [1, 64, 512, 512]
  - [1, 128, 1024, 1024]

IBM Platform LSF

You can run the pipeline on an LSF cluster by specifying the --cluster=lsf parameter. For example:

export INPUT=/path/to/input
export OUTPUT=/path/to/output.zarr
export LOGDIR=`pwd`
bsub -n 4 -P myproject -o $LOGDIR/jobout.log -e $LOGDIR/joberr.log "/misc/sc/pixi run zarrify --src=$INPUT --dest=$OUTPUT --cluster $CLUSTER --log_dir $LOGDIR/workers --workers 500 --zarr_chunks 3 128 128 128 --extra_directives='-P myproject' --scale 1.0 1.0 0.116 0.116 --optimize_reads"

Python API

Integrating conversion to zarr into the python code

import zarrify
from zarrify.utils.dask_utils import initialize_dask_client

client = initialize_dask_client("local") # or "lsf"
zarrify.to_zarr("input.mrc", "output.zarr", client, workers=20)

Supported formats

• TIFF stacks
• 3D TIFF files
• MRC files
• N5 containers