Skip Navigation

This Article
Right arrow FREE Full Text (Print PDF) Freely available
Right arrow FREE Full Text (Screen PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Hall, D.
Right arrow Articles by Jiang, T.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Hall, D.
Right arrow Articles by Jiang, T.
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Bioinformatics Vol. 17 no. 3 2001
Pages 205-213
© 2001 Oxford University Press


Original Paper

Physical mapping with automatic capture of hybridization data

David Hall 1,2, Suchendra M. Bhandarkar 1,*, Jonathan Arnold 2 and Tongzhang Jiang 1

1 Department of Computer Science
2 Department of Genetics, The University of Georgia, Athens, GA 30602, USA

Received on June 23, 2000 ; revised on October 25, 2000 ; accepted on November 20, 2000

Motivation: Contig maps are a type of physical map that show the native order of a set of overlapping genomic clones. Overlaps between clones can be detected by finding common sequences using a number of experimental protocols including hybridization of probes. All current mapping algorithms of which we are aware require that hybridizations be scored using a fixed number of discrete values (typically 0/1 or high/medium/low). When hybridization data is captured automatically using digital equipment, this provides the opportunity for hybridization intensities to be used in map construction. More fine-grained distinctions in the levels of hybridization may be exploited by algorithms to generate more accurate physical maps.

Results: We describe an approach to creating contig maps that uses measured hybridization intensities instead of data scored with a fixed number of discrete values. We describe and compare four algorithms for creating physical maps with hybridization intensities. Simulations using measured intensities sampled from actual data on Aspergillus nidulans indicate that using hybridization intensities rather than data that is automatically scored with respect to threshold values may yield more accurate physical maps.

Availability: All software programs described in this paper may be obtained by contacting the authors.

Contact: suchi{at}cs.uga.edu

* To whom correspondence should be addressed.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?




Disclaimer:
Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.