Accommodating error analysis in comparison and clustering of molecular fingerprints.

Details

• Alternative Title:
  Emerg Infect Dis
• Personal Author:
  Salamon, H. ; Segal, M. R. ; Ponce de Leon, A. ; Small, P. M.
• Description:
  Molecular epidemiologic studies of infectious diseases rely on pathogen genotype comparisons, which usually yield patterns comprising sets of DNA fragments (DNA fingerprints). We use a highly developed genotyping system, IS6110-based restriction fragment length polymorphism analysis of Mycobacterium tuberculosis, to develop a computational method that automates comparison of large numbers of fingerprints. Because error in fragment length measurements is proportional to fragment length and is positively correlated for fragments within a lane, an align-and-count method that compensates for relative scaling of lanes reliably counts matching fragments between lanes. Results of a two-step method we developed to cluster identical fingerprints agree closely with 5 years of computer-assisted visual matching among 1,335 M. tuberculosis fingerprints. Fully documented and validated methods of automated comparison and clustering will greatly expand the scope of molecular epidemiology.
• Subjects:
  Algorithms Computer Simulation Dna Fingerprinting Genotype Humans Molecular Epidemiology Mycobacterium Tuberculosis Polymorphism, Restriction Fragment Length Tuberculosis
• Source:
  Emerg Infect Dis. 4(2):159-168.
• Document Type:
  Journal Article
• Volume:
  4
• Issue:
  2
• Collection(s):
  Emerging Infectious Diseases
• Main Document Checksum:
  urn:sha256:f9e7affc91145edf38b74378eaa1503f19e96e0e9dc96f573005f9dcbf3e9394
• Download URL:
  https://stacks.cdc.gov/view/cdc/15479/cdc_15479_DS1.pdf
• File Type:
  [PDF - 107.64 KB ]