IMperm

IMperm merges paired-end (PE) reads derived from adaptive immune receptor repertoire (AIRR) sequencing to reconstruct T-cell and B-cell receptor sequences for applications in cancer immunotherapy and minimal residual disease (MRD) detection in leukemia and lymphoma.

Key Features:

• K-mer-and-Vote Strategy: Employs a k-mer-and-vote strategy to identify overlapping regions between paired-end reads for efficient merging.
• Versatility in Handling PE Reads: Processes PE reads including low-quality or minor/non-overlapping segments and removes adapter contamination to preserve merged sequence integrity.
• Performance Superiority: Outperforms existing tools on simulated and real sequencing datasets, demonstrating robustness and reliability.
• MRD Detection Results: Identified 19 novel MRD clones across 14 leukemia patients in previously published data.
• Broad Applicability: Effective with PE reads from other genomic sources and cell-free DNA datasets.
• Efficiency in Resource Utilization: Implemented in the C programming language and optimized for minimal runtime and memory consumption.

Scientific Applications:

• MRD detection in leukemia and lymphoma: Supports identification and tracking of MRD clones from AIRR sequencing data.
• Cancer immunotherapy: Enables analysis of T-cell and B-cell receptor repertoires relevant to immunotherapy studies.
• Genomic and cell-free DNA analyses: Merges PE reads from other genomic sources and cell-free DNA to support diverse genomic investigations.

Methodology:

Uses a k-mer-and-vote strategy to identify overlaps between paired-end reads, performs adapter contamination removal, and is implemented in the C programming language.