Error Checking and Graphical Representation of Multiple–Complete–Digest (MCD) Restriction-Fragment Maps

AUTOR(ES)
FONTE

Cold Spring Harbor Laboratory Press

RESUMO

Genetic and physical maps display the relative positions of objects or markers occurring within a target DNA molecule. In constructing maps, the primary objective is to determine the ordering of these objects. A further objective is to assign a coordinate to each object, indicating its distance from a reference end of the target molecule. This paper describes a computational method and a body of software for assigning coordinates to map objects, given a solution or partial solution to the ordering problem. We describe our method in the context of multiple–complete–digest (MCD) mapping, but it should be applicable to a variety of other mapping problems. Because of errors in the data or insufficient clone coverage to uniquely identify the true ordering of the map objects, a partial ordering is typically the best one can hope for. Once a partial ordering has been established, one often seeks to overlay a metric along the map to assess the distances between the map objects. This problem often proves intractable because of data errors such as erroneous local length measurements (e.g., large clone lengths on low-resolution physical maps). We present a solution to the coordinate assignment problem for MCD restriction-fragment mapping, in which a coordinated set of single-enzyme restriction maps are simultaneously constructed. We show that the coordinate assignment problem can be expressed as the solution of a system of linear constraints. If the linear system is free of inconsistencies, it can be solved using the standard Bellman–Ford algorithm. In the more typical case where the system is inconsistent, our program perturbs it to find a new consistent system of linear constraints, close to those of the given inconsistent system, using a modified Bellman–Ford algorithm. Examples are provided of simple map inconsistencies and the methods by which our program detects candidate data errors and directs the user to potential suspect regions of the map.

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