Detecting Structural Variation in DNA Segments Helps to Diagnose Cancer
Statistical software that detects structural variations such as large insertions and deletions in short segments (reads) of DNA, can be used to diagnose cancer. Structural variations in short segments (reads) of DNA occur in complex diseases, such as cancer. To use these variations in diagnoses, the process of reading the DNA segments needs to be fast and inexpensive. The fast mapping algorithm maps each read to a reference genome; data mining and statistical analysis techniques are used to detect structural variations, such as large insertions or deletions.
Rapid Comparison with a Reference Genome
Second generation DNA sequencing techniques allow for rapid sequencing of short segments of DNA. The fast mapping algorithm compares each DNA read with the location on a reference genome. This automated technique is much quicker than current ad hoc techniques and requires much lower coverage of the genome than current methods.
BENEFITS OF FAST MAPPING ALGORITHM FOR DETECTING STRUCTURAL VARIATION IN DNA:
- Does not rely on complete coverage of the genome
- Analysis is automated rather than ad-hoc
- Can be used to diagnose complex diseases such as cancer
Phase of Development Prototype algorithms are functional but need to be bundled with sequencing machines.