SeqSeg

SeqSeg detects and localizes copy-number alterations (CNAs) in genomic sequences using massively parallel sequencing data for precise breakpoint mapping in cancer genomics.

Key Features:

• CNA detection and localization: Detects and localizes copy-number alterations, including gains and losses of DNA segments, from massively parallel sequencing reads.
• Segmentation: Segments sequences into regions of equal copy number to delineate CNA boundaries.
• Breakpoint resolution: Localizes breakpoints typically to approximately 1 kilobase.
• Statistical power analysis: Performs statistical analysis that evaluates the power to detect CNAs of various sizes, supporting assessments of sensitivity and specificity.
• Recurrent CNA identification: Identifies genomic regions with recurrent CNAs to assist in discovery of cancer-causing genes.
• Comparison to DNA microarrays: Provides over twofold improvement in breakpoint localization precision compared with DNA microarrays while maintaining comparable power to detect CNAs.
• Data scale: Operates on a collection of approximately 14 million aligned sequence reads from human cell lines.
• Experimental validation: Validated using experimental data from three matched pairs of tumor and normal cell lines.

Scientific Applications:

• Cancer gene discovery: Facilitates discovery of cancer-causing genes by mapping recurrent CNAs.
• Cancer genomics: Enables identification and characterization of genomic regions associated with oncogenesis and disease through precise CNA analysis.
• Breakpoint mapping: Supports detailed study of structural rearrangements and gene dosage effects via high-resolution breakpoint localization.

Methodology:

Segments aligned massively parallel sequence reads into equal-copy-number regions, applies statistical analyses to evaluate detection power across CNA sizes, and estimates breakpoint locations at approximately 1 kilobase resolution using ~14 million aligned reads.