Abstract
BackgroundThe Sulston score is a well-established, though approximate metric for probabilistically evaluating postulated clone overlaps in DNA fingerprint mapping. It is known to systematically over-predict match probabilities by various orders of magnitude, depending upon project-specific parameters. Although the exact probability distribution is also available for the comparison problem, it is rather difficult to compute and cannot be used directly in most cases. A methodology providing both improved accuracy and computational economy is required.ResultsWe propose a straightforward algebraic correction procedure, which takes the Sulston score as a provisional value and applies a power-law equation to obtain an improved result. Numerical comparisons indicate dramatically increased accuracy over the range of parameters typical of traditional agarose fingerprint mapping. Issues with extrapolating the method into parameter ranges characteristic of newer capillary electrophoresis-based projects are also discussed.ConclusionAlthough only marginally more expensive to compute than the raw Sulston score, the correction provides a vastly improved probabilistic description of hypothesized clone overlaps. This will clearly be important in overlap assessment and perhaps for other tasks as well, for example in using the ranking of overlap probabilities to assist in clone ordering.
Highlights
The Sulston score is a well-established, though approximate metric for probabilistically evaluating postulated clone overlaps in DNA fingerprint mapping
Fingerprint mapping continues to play an important role in large-scale DNA sequencing efforts [1,2,3,4,5]
While reasonable solutions have been found for many of these, one task that remains problematic is assessing postulated clone overlaps based on their fingerprint similarity
Summary
The Sulston score is a well-established, though approximate metric for probabilistically evaluating postulated clone overlaps in DNA fingerprint mapping. The exact probability distribution is available for the comparison problem, it is rather difficult to compute and cannot be used directly in most cases. Fingerprint mapping continues to play an important role in large-scale DNA sequencing efforts [1,2,3,4,5]. The "overlap problem", as this is often referred to, basically involves examining all pairwise clone comparisons in order to identify overlaps. The number of matching fragment lengths between the two associated fragment lists is established. A case having μ > 0 matches indicates a possible overlap because the mutual length(s) may represent the same DNA. Such matches are not conclusive indicators of overlap. One or more quantitative metrics are used to evaluate the authenticity (page number not for citation purposes)
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