The lumi Bioconductor package, www.bioconductor.org

The Gene Ontology (GO) project (http://www. geneontology.org/) provides structured, controlled vocabularies and classifications that cover several domains of molecular and cellular biology and are freely available for community use in the annotation of genes, gene products and sequences. Many model organism databases and genome annotation groups use the GO and contribute their annotation sets to the GO resource. The GO database integrates the vocabularies and contributed annotations and provides full access to this information in several formats. Members of the GO Consortium continually work collectively, involving outside experts as needed, to expand and update the GO vocabularies. The GO Web resource also provides access to extensive documentation about the GO project and links to applications that use GO data for functional analyses.

BackgroundHigh-throughput profiling of DNA methylation status of CpG islands is crucial to understand the epigenetic regulation of genes. The microarray-based Infinium methylation assay by Illumina is one platform for low-cost high-throughput methylation profiling. Both Beta-value and M-value statistics have been used as metrics to measure methylation levels. However, there are no detailed studies of their relations and their strengths and limitations.ResultsWe demonstrate that the relationship between the Beta-value and M-value methods is a Logit transformation, and show that the Beta-value method has severe heteroscedasticity for highly methylated or unmethylated CpG sites. In order to evaluate the performance of the Beta-value and M-value methods for identifying differentially methylated CpG sites, we designed a methylation titration experiment. The evaluation results show that the M-value method provides much better performance in terms of Detection Rate (DR) and True Positive Rate (TPR) for both highly methylated and unmethylated CpG sites. Imposing a minimum threshold of difference can improve the performance of the M-value method but not the Beta-value method. We also provide guidance for how to select the threshold of methylation differences.ConclusionsThe Beta-value has a more intuitive biological interpretation, but the M-value is more statistically valid for the differential analysis of methylation levels. Therefore, we recommend using the M-value method for conducting differential methylation analysis and including the Beta-value statistics when reporting the results to investigators.

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We developed OligoCalc as a web-accessible, client-based computational engine for reporting DNA and RNA single-stranded and double-stranded properties, including molecular weight, solution concentration, melting temperature, estimated absorbance coefficients, inter-molecular self-complementarity estimation and intra-molecular hairpin loop formation. OligoCalc has a familiar ‘calculator’ look and feel, making it readily understandable and usable. OligoCalc incorporates three common methods for calculating oligonucleotide-melting temperatures, including a nearest-neighbor thermodynamic model for melting temperature. Since it first came online in 1997, there have been more than 900 000 accesses of OligoCalc from nearly 200 000 distinct hosts, excluding search engines. OligoCalc is available at http://basic.northwestern.edu/biotools/OligoCalc.html, with links to the full source code, usage patterns and statistics at that link as well.