Clustering competition binding ELISAs and/or neutralization experiments

Code to cluster fitted sigmoidal curves as described in manuscript "Two point mutations in protocadherin-1 disrupt Andes hantavirus recognition and afford protection against lethal infection" by Megan M. Slough et al.

1. img: Images for readme file
2. input: Experimental data
   • competition_ELISAs_EC1_mutants: Competition binding ELISAs
   • neutralization_EC1_mutants: Neutralization data
3. output: Output files generated by scripts
   • competition_clustering: Output generated by "clustering.ipynb"
   • competition_fitted_sigmoidal_readouts.csv: Expected readouts inferred from the fitted sigmoidal
   • competition_normalized.xlsx: Output generated by "normalize_by_last_column.ipynb"
   • competition_clustering: Output generated by "clustering.ipynb"
   • competition_fitted_sigmoidal_readouts.csv: Expected readouts inferred from the fitted sigmoidal
   • competition_normalized.xlsx: Output generated by "normalize_by_last_column.ipynb"
4. scr: script directory
   • normalize_by_last_column.ipynb: Normalize the experimental readouts by the last column ("Control")
     • Input: Raw data in the "input" directory
     • Output: Xlsx file with normalized readouts
   • clustering.ipynb: Clustering fitted sigmoidal curves
     • Input: Expected readouts inferred from the fitted sigmoidal
     • Output: Hierarchical clustering of fitted sigmoidals, including k cluster extraction (k goes from 2 to 10)