Introduction to the Workshop
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The electronic form of this document may be cited in the following style:
Human Genome Program, U.S. Department of Energy, DOE Human Genome Program Contractor-Grantee Workshop IV, 1994.
Abstracts scanned from text submitted for November 1994 DOE Human Genome Program Contractor-Grantee Workshop. Inaccuracies have not been corrected.
On Generating Accurate Transposon Maps
E. Veklerov, C. Martin, E. Theil
Human Genome Center, Lawrence Berkeley Laboratory, Berkeley, CA 94720
Generation of transposon maps is an important step in the directed sequencing strategy used at LBL. The accuracy of the map affects the success of the assembly process, and thus the per-base cost of the final sequence. We have designed and developed a software package called TRAMP that generates such maps. It also helps researchers study the algorithms involved in this process in order to explore and optimize them.
TRAMP is a highly interactive software package written in Smalltalk,which is an object oriented language that has convenient facilities for handling graphical interface applications. The central part of the package is its selection algorithm which finds a subset of the inserts that, being subsequently used as the priming sites, has a high probability of covering the clone without gaps. At present, manually generated maps alone result in an average coverage (doublestranded) of 93% of an individual 3kb clone. Automatically generated maps take much less time to generate, are more accurate and should reduce both the number of gaps and their average length. We have developed an algorithm that finds a minimum number of inserts which cover the clone and is optimal in the sense that these inserts are distributed as uniformly as possible within the clone.
Another function facilitated by TRAMP is "post-mortem" studies of the transposon maps. After a clone is fully assembled, the positions of the inserts are known exactly and can be compared with the original positions that were estimates based on PCR reations. A preliminary study has shown that the discrepancies between the estimated and actual positions may be on the order of about 10%. A comparison of "before" and "after" maps will help to identify sources of systematic errors, eliminate at least some of them and eventually reduce the cost of sequencing.