AStra

AStra estimates genome-wide aneuploidy profiles from raw whole-genome sequencing (WGS) reads using read depth (RD) analyses to produce digital karyotypes for cancer cell line authentication and quality assessment, and it is implemented in Python.

Key Features:

• De Novo Aneuploidy Estimation: Estimates copy number at every genomic locus directly from raw WGS reads.
• Read-Depth (RD) Analysis: Applies RD-based computational analyses to infer locus-specific copy number and genome-wide aneuploidy.
• Digital Karyotyping Prototype: Generates digital karyotypes that provide signatures to differentiate clonal variants or strains of cell lines.
• Visualization Tools: Produces visual comparisons of aneuploidy profiles across cell lines or strains.
• Implementation: Implemented in Python.

Scientific Applications:

• Cell Line Authentication: Uses genome-wide aneuploidy profiles to authenticate cancer cell lines.
• Clonal Variant Discrimination: Distinguishes clonal variants or strains by unique digital karyotype signatures.
• Quality Assessment and Contamination Detection: Enables first-pass quality assessment to detect genetic drift and cross-contamination in cell line stocks.

Methodology:

Applies read depth (RD)-based computational analyses to WGS data to estimate copy number at each genomic locus; validation was performed using simulated datasets and various cancer cell lines.