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Data Processing

The processing package prepares data for KinOpt and maps optimization outputs into network-oriented tables.

Package Structure

processing/
├── __init__.py
├── cleanup.py
├── input1_wstd.csv
├── map.py
└── raw/

processing.cleanup

cleanup.py prepares time-series input files from raw CSV data in processing/raw/.

Typical responsibilities include:

  • Cleaning interaction records.
  • Transforming phosphoproteomics and transcriptomics time-series values.
  • Propagating standard deviations where available.
  • Producing standardized CSV inputs for KinOpt workflows.

processing.map

map.py maps optimization results back to kinase-substrate and phosphorylation-site relationships.

Typical responsibilities include:

  • Reading KinOpt result tables.
  • Extracting non-zero or relevant optimization coefficients.
  • Producing edge and node tables for downstream network inspection.
  • Adding kinetic strength information to mapped relationships.

Raw Inputs

Raw input files are expected under processing/raw/. The exact files depend on the workflow, but this repository contains examples such as:

  • CollecTRI.csv
  • MS_Gaussian_updated_09032023.csv
  • Rout_LimmaTable.csv
  • input2.csv

Outputs

Processing outputs are standardized CSV files used by KinOpt optimization and downstream analysis. Keep generated files out of documentation unless they are stable examples checked into the repository.