tcpl: the ToxCast pipeline for high-throughput screening data.

Area of Science:

• Computational chemistry
• Bioinformatics
• Toxicology

Background:

• Large-scale chemical screening is crucial for drug development and toxicity assessment.
• Integrating and analyzing high-throughput screening (HTS) data requires efficient and reproducible pipelines.

Purpose of the Study:

• To introduce the tcpl R package and its associated MySQL database as a generalized platform.
• To provide tools for efficient storage, normalization, and dose-response modeling of HTS data.

Main Methods:

• Development of the tcpl R package and a complementary MySQL database.
• Implementation of a novel dose-response modeling algorithm.
• Testing the algorithm against millions of diverse dose-response series.

Main Results:

• The tcpl package facilitates efficient data management for HTS.
• The novel algorithm demonstrates robustness in fitting dose-response data, including outliers and signal loss.
• The platform supports transparency and reproducibility in chemical screening data analysis.

Conclusions:

• The tcpl R package provides a generalized and efficient solution for HTS data analysis.
• The platform enhances the utility of large chemical screening datasets in drug development and toxicity screening.
• The developed modeling algorithm is effective for complex and noisy dose-response data.