MOTIVATION: Array Comparative Genomic Hybridization (CGH) can reveal chromosomal aberrations in the genomic DNA. These amplifications and deletions at the DNA level are important in the pathogenesis of cancer and other diseases. While a large number of approaches have been proposed for analyzing the large array CGH datasets, the relative merits of these methods in practice are not clear. RESULTS: We compare 11 different algorithms for analyzing array CGH data. These include both segment detection methods and smoothing methods, based on diverse techniques such as mixture models, Hidden Markov Models, maximum likelihood, regression, wavelets and genetic algorithms. We compute the Receiver Operating Characteristic (ROC) curves using simulated data to quantify sensitivity and specificity for various levels of signal-to-noise ratio and different sizes of abnormalities. We also characterize their performance on chromosomal regions of interest in a real dataset obtained from patients with Glioblastoma Multiforme. While comparisons of this type are difficult due to possibly sub-optimal choice of parameters in the methods, they nevertheless reveal general characteristics that are helpful to the biological investigator.

This paper describes an approach that provides Internet-based support for a genome center to map human chromosome 12, as a collaboration between laboratories at the Albert Einstein College of Medicine in Bronx, New York, and the Yale University School of Medicine in New Haven, Connecticut. Informatics is well established as an important enabling technology within the genome mapping community. The goal of this paper is to use the chromosome 12 project as a case study to introduce a medical informatics audience to certain issues involved in genome informatics and in the Internet-based support of collaborative bioscience research. Central to the approach described is a shared database (DB/12) with Macintosh clients in the participating laboratories running the 4th Dimension database program as a user-friendly front end, and a Sun SPARCstation-2 server running Sybase. The central component of the database stores information about yeast artificial chromosomes (YACs), each containing a segment of human DNA from chromosome 12 to which genome markers have been mapped, such that an overlapping set of YACs (called a "contig") can be identified, along with an ordering of the markers. The approach also includes 1) a map assembly tool developed to help biologists interpret their data, proposing a ranked set of candidate maps, 2) the integration of DB/12 with external databases and tools, and 3) the dissemination of the results. This paper discusses several of the lessons learned that apply to many other areas of bioscience, and the potential role for the field of medical informatics in helping to provide such support.