We developed Gene Interaction Matrices (GIM) as a biologically inspired, gene-interaction based data transformation on gene expression data to create an image-like feature matrix from any gene expression-based study. The transformed data can then be used with any CNN based machine learning approaches for a variety of challenging problems such as disease diagnostics and drug development.

python >= 3.7
numpy 1.20.3
pandas 1.3.0

An example workflow to create a GIM is described here. To begin import the necessary dependencies and gim .py file containing the transform function.

import pandas
import gim

Load the treatment and control files containing one or more replicates from the gim/data/ directory.

df_control_replicates = pd.read_csv("control_replicates.csv")
df_treatment_replicates = pd.read_csv("treatment_replicates.csv")

Apply the gim_transform function to the files.

sample_img = gim.gim_transform(df_control_replicates, df_treatement_replicates)

Pre-print: https://www.biorxiv.org/content/10.1101/2021.09.07.459284v1