Sulston Score¶
A classical physical-mapping tail score that estimates, under a uniform independent-band null model, the chance of observing at least as many fragment-size matches as two clone fingerprints actually share.
Core Idea¶
The Sulston Score is a classical chance-overlap statistic for restriction-fragment clone fingerprints in physical genome mapping. It asks a tightly bounded question: if two unrelated clones produced fragment positions under a simple uniform random model, what is the probability that their fingerprints would show at least the observed number of size matches? A smaller score makes the observed agreement harder to explain as random coincidence and therefore supports—without proving—the hypothesis that the clones overlap in genomic sequence.
Scope of Application¶
The home setting is clone-based physical genome mapping: large-insert clones are restriction digested, their fragment patterns are measured, and pairwise similarities are used to propose overlaps and assemble contigs. The original 1988 software work arose in automated genome mapping by fingerprinting, and the 1997 FPC paper formalized a system for clustering restriction-fingerprinted clones into contigs and supporting a minimal tiling path.
The abstraction applies when fingerprints can be represented as comparable fragment-size lists and a project declares a resolution or tolerance model. It was especially natural for gel-based restriction fingerprints and was subsequently discussed for high-throughput and capillary-electrophoresis conditions.
Clarity¶
To identify a Sulston-score claim, ask four questions. First, are the inputs two clone fragment fingerprints rather than sequences or generic feature vectors? Second, is a fragment-size matching tolerance or bin model explicit? Third, is the output the probability of at least the observed match count under an unrelated-clone chance model? Fourth, is the classical independence approximation acknowledged?
Manages Complexity¶
A physical map with \(N\) clones presents \(N(N-1)/2\) possible pairs. Raw inspection of every pair's fragment lists does not scale, and a match count is not comparable across clones with different numbers of bands or different measurement resolution. The Sulston Score compresses each pair into a common ordered quantity that incorporates those factors. Algorithms can rank candidate neighbors, discard implausible pairs, form tentative contigs, and send ambiguous cases to human review.
Abstract Reasoning¶
The formula licenses several useful deductions. Holding \(m\), \(n\), and \(B\) fixed, increasing \(h\) can only decrease or leave unchanged the right-tail score, so more observed matches give no weaker classical evidence. Holding \(h\), \(n\), and \(B\) fixed, increasing \(m\) raises the chance that any target band finds a match and can make the same \(h\) less surprising. Finer resolution—larger \(B\), or smaller \(r/G\)—lowers the chance-match probability under the model, although real gains can be limited when laboratory error or dependence remains.
Knowledge Transfer¶
Literal transfer occurs across gel fingerprinting, high-throughput clone fingerprinting, physical-map construction, contig review, and clone ordering so long as the band-list and resolution model remain meaningful. The same score can be computed in different software because its mathematical roles are separable from its implementation.
Beyond physical mapping, the skeleton—represent two objects, count matches, specify a chance model, compute a tail, and threshold or rank—resembles record linkage, forensic matching, and similarity search. Those are analogies, not additional Sulston-score instances.
Relationships to Other Abstractions¶
Current abstraction Sulston Score Domain-specific
Parents (1) — more general patterns this builds on
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Sulston Score is a kind of Statistical Significance (p-Value) Prime
The Sulston Score strictly instantiates
prime:statistical_significance_p_value: it is a tail probability of a match-count statistic under a stated chance null and is read as evidence against that null.
Hierarchy paths (11) — routes to 5 parentless roots
- Sulston Score → Statistical Significance (p-Value) → Statistical Inference → Inductive Reasoning
- Sulston Score → Statistical Significance (p-Value) → Statistical Inference → Uncertainty
- Sulston Score → Statistical Significance (p-Value) → Hypothesis Testing (Null vs. Alternative) → Statistical Inference → Inductive Reasoning
- Sulston Score → Statistical Significance (p-Value) → Probability → Measure → Set and Membership
- Sulston Score → Statistical Significance (p-Value) → Hypothesis Testing (Null vs. Alternative) → Statistical Inference → Uncertainty
- Sulston Score → Statistical Significance (p-Value) → Probability → Measure → Aggregation → Micro Macro Linkage
- Sulston Score → Statistical Significance (p-Value) → Statistical Inference → Probability → Measure → Set and Membership
- Sulston Score → Statistical Significance (p-Value) → Statistical Inference → Probability → Measure → Aggregation → Micro Macro Linkage
- Sulston Score → Statistical Significance (p-Value) → Hypothesis Testing (Null vs. Alternative) → Verification → Evaluation → Comparison → Self Checking
- Sulston Score → Statistical Significance (p-Value) → Hypothesis Testing (Null vs. Alternative) → Statistical Inference → Probability → Measure → Set and Membership
- Sulston Score → Statistical Significance (p-Value) → Hypothesis Testing (Null vs. Alternative) → Statistical Inference → Probability → Measure → Aggregation → Micro Macro Linkage
Neighborhood in Abstraction Space¶
Sulston Score sits in a sparse region of the domain-specific corpus (99th percentile for distinctiveness): few abstractions share its structure, so a faithful description tends to retrieve it precisely.
Family — Unclustered & Miscellaneous (1565 abstractions)
Nearest neighbors
- Hunt–Szymanski Algorithm — 0.75
- Gower's Distance — 0.74
- Gap Penalty — 0.74
- Wilf Equivalence — 0.74
- Normal Order of an Arithmetic Function — 0.74
Computed from structural-signature embeddings · 2026-09-08