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https://github.com/bioinfotongli/workflow-decoding

Decoding of image-based spatial transcriptomics

https://github.com/bioinfotongli/workflow-decoding

Science Score: 13.0%

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Repository

Decoding of image-based spatial transcriptomics

Basic Info
  • Host: GitHub
  • Owner: BioinfoTongLI
  • License: mit
  • Language: Jupyter Notebook
  • Default Branch: master
  • Size: 28.2 MB
Statistics
  • Stars: 1
  • Watchers: 0
  • Forks: 1
  • Open Issues: 0
  • Releases: 1
Created over 5 years ago · Last pushed about 1 year ago
Metadata Files
Readme License

README.md

Image-based spatial transcritomics RNA spot decoding workflow

This workflow includes: - Raw image enchancement with White Tophat filtering - Peak-calling with TrackPy - PoSTcode decoding: plot which is a method for decoding image-based spatial transcriptomics based on a re-parametrised matrix-variate Gaussian mixture model,

Prerequisite: - Nextflow - Docker/singularity

Usage (TODO):

bash NXF_OPTS='-Dleveldb.mmap=false' NXF_VER=23.10.1 \ nextflow -trace nextflow.executor run BioinfoTongLI/workflow-decoding -r master \ -profile local \ -params-file decoding.yaml An example of the parameter input file is yaml codebook : [codebook.csv] out_dir : [output folder] ome_zarr : [ome-zarr path of a registered multicycle multichannel stack] channel_map : "{'Cy5':'A','AF488':'G','Cy3':'C','Atto425':'T','AF750':'T'}" rna_spot_size : [5] anchor_ch_indexes : 1 prob_threshold : 0.9 trackpy_percentile : [90] trackpy_separation : 3 codebook_sep : ','

Owner

  • Name: Tong LI
  • Login: BioinfoTongLI
  • Kind: user
  • Location: Hinxton
  • Company: Wellcome Sanger Institute

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Dependencies

requirements.txt pypi
  • joblib *
  • jupyter *
  • jupyter_http_over_ws *
  • jupyterlab *
  • matplotlib *
  • pandas *
  • pdbpp *
  • pip *
  • pyro-ppl *
  • scikit-image ==0.15.0
  • scipy *
  • setuptools *
  • sklearn *
  • starfish ==0.2.2
  • tifffile *
  • torch *
  • torchvision *
  • trackpy *