INSTA

The INSTA pipeline uses crowd-sourced annotations for spot detection in RNA in situ transcriptomics images. This pipeline is described in detail in the paper Validation and tuning of in situ transcriptomics image processing workflows with crowdsourced annotations.

The directory demos contains notebooks that demonstrate INSTA's preprocessing and postprocessing functionality.

The directory instapipeline contains the codebase.

• BaseAnnotation.py contains the BaseAnnotation class, which has the tools for annotation injestion
• QuantiusAnnotation.py inherits from the BaseAnnotation class and implements annotation injestion for annotations from Quanti.us
• SpotAnnotationAnalysis.py contains methods for clustering and keeping track of whether a certain clustering for a given dataset has already been executed (to avoid redundant computations)
• param.py contains functions for parameter extraction
• autocrop.py contains functions for autocropping input images
• clus.py contains functions for
  • sorting clusters by size
  • sorting clusters by clumpiness and declumping
  • other cluster analyses
• vis.py contains functions for visualizing annotations and clusters
• util.py contains functions for:
  • interacting with / manipulating dataframes
  • other data structure manipulation

This repository is owned by the Bioengineering Platform.

Installation

instapipeline supports python 3.6 and 3.7. To install instapipeline, first verify that your python version is compatible by running python -version.

• Create a new anaconda environment: conda create --name <environment name> python=3.7
• Enter the new environment: conda activate <environment name>
• Install jupyter notebook: conda install -c conda-forge notebook
• Clone the instapipeline repo
• Install: pip install <path to directory with setup.py>