RaScALL

RaScALL rapidly screens RNA-sequencing (RNA-seq) data to detect prognostically significant genomic alterations in acute lymphoblastic leukaemia (ALL).

Key Features:

• k-mer Based Variant Detection: Uses a k-mer based variant detection approach leveraging the tool km to identify over 100 prognostically significant lesions from RNA-seq data, including gene fusions, single nucleotide variants (SNVs), and focal gene deletions.
• Comprehensive Genomic Alteration Identification: Detects a wide range of genomic alterations including challenging gene fusions such as EPOR and DUX4, with gene fusions detected in 98% of reported cases in the study cohort and 95% in the validation cohort.
• Pathogenic Variant Detection: Identifies pathogenic sequence variants including PAX5 p.P80R and IKZF1 p.N159Y and accurately detects intragenic IKZF1 deletions that produce aberrant transcript isoforms with 98% accuracy.
• Efficiency: Performs targeted alteration detection with an average analysis time of 22 minutes per sample, compared against standard alignment-based approaches.

Scientific Applications:

• Clinical diagnostics in ALL: Integrates RNA-seq data to support diagnostic risk stratification and treatment decision-making by identifying subtype-defining genomic alterations.
• Personalized medicine and research: Enables rapid detection and precise characterization of genetic changes such as gene fusions and pathogenic SNVs to inform treatment strategies and cohort validation studies.

Methodology:

Applies k-mer based variant detection via the km tool and was evaluated by comparison with alignment-based de novo variant detection tools across a study cohort of 180 Australian patient samples and a validation cohort of 100 North American patient samples.