MOTIVATION: Copy number variations (CNVs) are a major source of genomic variability and are especially significant in cancer. Until recently microarray technologies have been used to characterize CNVs in genomes. However, advances in next-generation sequencing technology offer significant opportunities to deduce copy number directly from genome sequencing data. Unfortunately cancer genomes differ from normal genomes in several aspects that make them far less amenable to copy number detection. For example, cancer genomes are often aneuploid and an admixture of diploid/non-tumor cell fractions. Also patient-derived xenograft models can be laden with mouse contamination that strongly affects accurate assignment of copy number. Hence, there is a need to develop analytical tools that can take into account cancer-specific parameters for detecting CNVs directly from genome sequencing data. RESULTS: We have developed WaveCNV, a software package to identify copy number alterations by detecting breakpoints of CNVs using translation-invariant discrete wavelet transforms and assign digitized copy numbers to each event using next-generation sequencing data. We also assign alleles specifying the chromosomal ratio following duplication/loss. We verified copy number calls using both microarray (correlation coefficient 0.97) and quantitative polymerase chain reaction (correlation coefficient 0.94) and found them to be highly concordant. We demonstrate its utility in pancreatic primary and xenograft sequencing data. AVAILABILITY AND IMPLEMENTATION: Source code and executables are available at https://github.com/WaveCNV. The segmentation algorithm is implemented in MATLAB, and copy number assignment is implemented Perl. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Relational database systems (RDBSs) are well-known and widely used in many organizations, however, semantic conflicts between the participating RDBSs must be resolved before data can be exchanged between them. Semantic resolution between the RDBSs is extremely difficult to address mainly because participating RDBSs are designed and built independently. Furthermore, individual RDBSs are likely to evolve over time and the changes must be reconciled dynamically. In this paper, we describe an approach to resolve the semantic conflicts between RDBSs automatically while allowing the individual RDBSs to evolve. Relational database ontology (RDBO) is created and used to ensure the semantic descriptions of the individual RDBSs are conformed to a set of vocabularies, structures, and restrictions. We show how a modified reasoning engine is used to validate and infer additional semantic relationships from the existing relationships. We also show how terms defined in different database ontologies are compared to each other semantically using semantic weights and our modified reasoning engine. As a result, RDBSs can intemperate with each other seamlessly and at the correct level of semantics defined in their ontologies.

UNLABELLED: Several semantic Web Services clients for Bioinformatics have been released, but to date no support systems for service providers have been described. We have created a framework ('MobyServlet') that very simply allows an existing Java application to conform to the MOBY-S semantic Web Services protocol. Using an existing Java program for codon-pair bias determination as an example, we enumerate the steps required for MOBY-S compliance. With minimal programming effort, such a deployment has the advantages of: (1) wider exposure to the user community by automatic inclusion in all MOBY-S client programs and (2) automatic interoperability with other MOBY-S services for input and output. Complex on-line analysis will become easier for biologists as more developers adopt MOBY-S. AVAILABILITY: The framework and documentation are freely available from the Java developer's section of http://www.biomoby.org/.