Skip to content

Code and data for validation studies of cycIF multiplex imaging platform

License

Notifications You must be signed in to change notification settings

smith6jt-cop/cycIF_Validation

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

80 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

cycIF_Validation

Code and data for validation of CyCIF multiplex imaging platform

Multiplex imaging technologies are increasingly used for single-cell phenotyping and spatial characterization of tissues; however, quantitative, reproducible analysis is a technical and computational challenge. We developed an open-source python-based image analysis tool, mplex-image, to achieve fully-reproducible multiplex image visualization and analysis. We deploy this tool in the accompanying Jupyter notebooks to validate specificity, sensitivity, reproducibility and normalization of the multiplex imaging platform cyclic immunofluorescence (CyCIF).

Through our work, we learned general principles of antibody staining performance, signal removal and background removal, and developed new methods, summarized below:

1. Signal removal using hydrogen peroxide

  • Inceased concentrations above 3% hydrogen peroxide do not improve speed of signal removal.
  • Increased incubation times of improve signal removal somewhat, but do not result in complete signal removal.
  • Increased heat of quenching solution results in complete signal removal but must be balanced with increased tissue loss.

2. Background autofluorescence removal

3. Antibody staining optimization and reproducibility

4. Methods

Binder

About

Code and data for validation studies of cycIF multiplex imaging platform

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 89.6%
  • Python 10.4%