NIPTeR

NIPTeR performs analysis of next-generation sequencing (NGS) data for non-invasive prenatal testing (NIPT) by reducing sample variability, performing quality-control assessments, characterizing non-trisomy control groups, and applying trisomy prediction algorithms to determine fetal trisomies.

Key Features:

• Configurable workflows: Create flexible analysis workflows tailored to specific research or diagnostic NIPT pipelines.
• Variation reduction: Implement methods to reduce inter-sample variability that can affect prediction accuracy.
• Trisomy prediction algorithms: Apply trisomy prediction algorithms to detect fetal chromosomal aneuploidies.
• Quality control and data integrity: Perform rigorous quality-control assessments of NGS data and evaluate data integrity.
• Control-group characterization: Calculate and enhance representativeness and statistical robustness of non-trisomy control groups.
• Variability management: Provide tools to align control-group characteristics with analyzed samples to improve consistency of results.

Scientific Applications:

• Laboratory NIPT processing: Process and assess NGS data for non-invasive prenatal testing workflows.
• Fetal trisomy detection: Support determination of the presence or absence of fetal trisomies from sequencing data.
• Control-group statistics: Enable precise calculation of control-group statistics to increase the reliability of trisomy predictions.

Methodology:

Construction of configurable workflows, reduction of sample variability, calculation and characterization of non-trisomy control-group statistics, application of trisomy prediction algorithms, and rigorous NGS quality-control and data-integrity assessments to determine fetal trisomies.