Genome mapping by nonrandom anchoring: a discrete theoretical analysis.

Zhang, M Q; Marr, Thomas G.

doi:10.1073/pnas.90.2.600

Cited by 17 publications

(11 citation statements)

References 16 publications

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“…We also give explicit, closed-form formulae for the case of constant length clones. Finally, in the case of constant length clones, we note that these results are equivalent to, and extend, previous published results of [71]. Simulations show these methods provide estimates well within the limits of uncertainty inherent in any mapping project.…”

Section: Total Coveragesupporting

confidence: 73%

“…First, however, we give a simple alternative "finite" analysis based on the distribution of spacings between the seed clones. This analysis, when simple approximations to integrals are used, can give results nearly identical to those by Zhang and Marr [71]. Next, following the lead of Arratia et a1 [2] and using properties of stationary processes, we derive simple asymptotic formulae which apply equally to constant and variable clone lengths.…”

Section: Total Coveragementioning

confidence: 69%

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Statistical methods in physical mapping

Nelson¹

1995

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DISCLAIMERThis document was prepared as an account of work sponsored by an agency ofthe United States Government.Neither the United States Government nor the University of California nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, producf or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial produds, process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by theunited StatesGovernment or theuniversity ofCalifornia. Theviewsand opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or the University of California, and shall not be used for advertising or product endorsement purposes.This report has been reproduced directly from the b e t available copy. The last chapter explores unsolved problems and describes future work.

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Section: Total Coveragesupporting

confidence: 73%

Section: Total Coveragementioning

confidence: 69%

Statistical methods in physical mapping

Nelson¹

1995

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“…Actual clone sizes in any library can be expected to vary somewhat; however, uniform clone size has been a standard theoretical assumption (e.g., Lander and Waterman 1988;Barillot et al 1991;Zhang and Marr 1993;Port et al 1995;Roach 1995). We use data from chromosome-2 BAC clones to evaluate the effect upon the present model.…”

Section: Assessment Of the Importance Of Clone Size Variationmentioning

confidence: 99%

“…As for mathematical modeling, the randomsequencing scenario described above has not been specifically addressed. Theoretical developments have concentrated mainly on mapping techniques, for example, the seminal work of Lander and Waterman (1988) for the fingerprint method and later models for other procedures (Arratia et al 1991;Barillot et al 1991;Zhang and Marr 1993;Port et al 1995;Schbath 1997). Owing to considerations of similarity, it has been postulated that mapping models could be directly applied to random clone sequencing (Lander and Waterman 1988;Roach 1995).…”

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confidence: 99%

Theories and Applications for Sequencing Randomly Selected Clones

Wendl¹

2001

Genome Research

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Theory is developed for the process of sequencing randomly selected large-insert clones. Genome size, library depth, clone size, and clone distribution are considered relevant properties and perfect overlap detection for contig assembly is assumed. Genome-specific and nonrandom effects are neglected. Order of magnitude analysis indicates library depth is of secondary importance compared to the other variables, especially as clone size diminishes. In such cases, the well-known Poisson coverage law is a good approximation. Parameters derived from these models are used to examine performance for the specific case of sequencing random human BAC clones. We compare coverage and redundancy rates for libraries possessing uniform and nonuniform clone distributions. Results are measured against data from map-based human-chromosome-2 sequencing. We conclude that the map-based approach outperforms random clone sequencing, except early in a project. However, simultaneous use of both strategies can be beneficial if a performance-based estimate for halting random clone sequencing is made. Results further show that the random approach yields maximum effectiveness using nonbiased rather than biased libraries.

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“…Palazzolo et al (1991) described one such methodology, a double-end, clone-limited strategy. Zhang and Marr (1993) developed an approximate theoretical model for a similar strategy, nonrandom clone anchoring. These two strategies are derivatives of the parking strategy, and our analyses hold in these cases.…”

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confidence: 99%

Parking Strategies for Genome Sequencing

Roach

Thórsson²,

Siegel³

2000

Genome Res.

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The parking strategy is an iterative approach to DNA sequencing. Each iteration consists of sequencing a novel portion of target DNA that does not overlap any previously sequenced region. Subject to the constraint of no overlap, each new region is chosen randomly. A parking strategy is often ideal in the early stages of a project for rapidly generating unique data. As a project progresses, parking becomes progressively more expensive and eventually prohibitive. We present a mathematical model with a generalization to allow for overlaps. This model predicts multiple parameters, including progress, costs, and the distribution of gap sizes left by a parking strategy. The highly fragmented nature of the gaps left after an initial parking strategy may make it difficult to finish a project efficiently. Therefore, in addition to our parking model, we model gap closing by walking. Our gap-closing model is generalizable to many other strategies. Our discussion includes modified parking strategies and hybrids with other strategies. A hybrid parking strategy has been employed for portions of the Human Genome Project.A large number and variety of strategies have been proposed and implemented for sequencing large genomes. Both mathematical and simulation models of these strategies are useful in conjunction with large-scale genome projects. These models serve three purposes. First, they allow projects to be planned efficiently, with appropriate allocation of resources, including estimates of project duration. Second, they allow the progress of projects to be monitored. Deviation of an observed parameter, such as target coverage, from its predicted value indicates a technical or biological problem, such as poor-quality data generation or the presence of unclonable regions on the target genome. Third, models allow for cost optimization. A mild increase in cost efficiency can result in tremendous absolute savings, given the overall high cost of large-scale genome sequencing. Costs can be optimized by choosing between alternative sequencing strategies, tuning controllable parameters such as clone-length distribution, and combing strategies to produce hybrid strategies.In this paper, we present a mathematical model for the parking strategy for genome sequencing. This strategy, in combination with other strategies, has been used for portions of the Human Genome Project and may prove popular for future genome projects for organisms with large genomes (Roach et al. 1999;Batzoglou et al. 1999). The name of the parking strategy derives from a mathematically equivalent scenario that has interested mathematicians for over 50 years (Solomon and Weiner 1986). The scenario consists of cars arriving sequentially to park along an infinite unmarked curb. Each car selects a spot along the curb to park with no regard for subsequent cars. As time proceeds, the curb fills. Any gap greater than a car length will eventually be occupied by a car, but if a gap between two cars is created that is less than the length of a car, it will remain forever em...

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Genome mapping by nonrandom anchoring: a discrete theoretical analysis.

Cited by 17 publications

References 16 publications

Statistical methods in physical mapping

Statistical methods in physical mapping

Theories and Applications for Sequencing Randomly Selected Clones

Parking Strategies for Genome Sequencing

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