PhosKinTime Data Preprocessing & Mapping

This workflow prepares and maps time-series data for kinase and transcription factor optimization models from raw proteomics and transcriptomics datasets.

Structure

phoskintime/
├── processing/
│   ├── cleanup.py     # Data cleaning and preparation
│   └── map.py         # Optimization result mapping and network table generation
├── raw/               # Input CSVs (CollecTRI, MS Gaussian, Rout Limma)
├── kinopt/data/       # Kinase model inputs
├── tfopt/data/        # TF model inputs
└── data/              # Network export for Cytoscape

Scripts Overview

cleanup.py

Performs the following steps:

  1. TF-mRNA Interaction Cleanup

    • Filters complex interactions in CollecTRI
    • Keeps only TFs matching phospho-interactions in input2.csv

  2. Proteomics Data Transformation

    • Transforms MS Gaussian predictions with 2^mean
    • Formats phosphorylation sites, saves to input1.csv

  3. Error Propagation

    • Computes std propagation:
      σ_y = 2^x * ln(2) * σ_x
    • Saves to input1_wstd.csv

  4. Transcriptomics Cleanup

    • Transforms Rout Limma values with 2^x
    • Saves to input3.csv

  5. Gene Symbol Mapping

    • Replaces Ensembl/Entrez IDs with gene symbols (using MyGeneInfo)

  6. File Management

    • Moves cleaned files to kinopt/data/ and tfopt/data/

map.py

This script processes optimization results for transcription factors (TFs) and kinases, mapping their interactions with mRNA and phosphorylation sites. It generates Cytoscape-compatible edge and node tables for network visualization.

Key Features:

  • TF-mRNA Mapping: Extracts non-zero optimization results and groups mRNA by associated TFs and their strengths.
  • Kinase-Phosphorylation Mapping: Maps kinases to mRNA and phosphorylation sites based on optimization results.
  • Cytoscape Table Generation: Creates edge and node tables for network visualization, including interaction types and strengths.
  • Kinetic Strength Integration: Adds kinetic strength columns to mapping files for further analysis.

Inputs

Place the following raw data in processing/raw/:

  • CollecTRI.csv
  • MS_Gaussian_updated_09032023.csv
  • Rout_LimmaTable.csv
  • input2.csv (phospho interactions)

Outputs

File Description
input1.csv Phospho time series (KinOpt, TFOpt)
input1_wstd.csv Same as above + standard deviation
input2.csv Phospho kinase-interaction metadata
input3.csv mRNA time series (TFOpt)
input4.csv Clean TF-mRNA interactions
mapping.csv Mapped TF → mRNA with Kinase + Psite
mapping_.csv Cytoscape-compatible edge list
nodes.csv Cytoscape node roles

Notes

  • Complex TF interactions (e.g. COMPLEX:TF1/TF2) are excluded.
  • Kinase-only proteins not appearing in CollecTRI (e.g. PAK2) are excluded from TF mapping.
  • Unmappable GeneIDs are printed at runtime.