High-throughput bioinformatics with the Cyrille2 pipeline system

BACKGROUND

Modern omics research involves the application of high-throughput technologies that generate vast volumes of data. These data need to be pre-processed, analyzed and integrated with existing knowledge through the use of diverse sets of software tools, models and databases. The analyses are often interdependent and chained together to form complex workflows or pipelines. Given the volume of the data used and the multitude of computational resources available, specialized pipeline software is required to make high-throughput analysis of large-scale omics datasets feasible.

RESULTS

We have developed a generic pipeline system called Cyrille2. The system is modular in design and consists of three functionally distinct parts: 1) a web based, graphical user interface (GUI) that enables a pipeline operator to manage the system; 2) the Scheduler, which forms the functional core of the system and which tracks what data enters the system and determines what jobs must be scheduled for execution, and; 3) the Executor, which searches for scheduled jobs and executes these on a compute cluster.

CONCLUSION

The Cyrille2 system is an extensible, modular system, implementing the stated requirements. Cyrille2 enables easy creation and execution of high throughput, flexible bioinformatics pipelines.

Post alignment clustering procedure for comparative quantitative proteomics LC-MS data

Comparative LC-MS is a powerful method for detailed quantitative comparison of complex protein mixtures. Dedicated software is required for detection, matching, and alignment of peaks in multiple LC-MS datasets. However, retention time shifts, saturation effects, limitations of experimental accuracy, and possible occurrence of split peaks make it difficult for software to perfectly match all chromatograms. We describe a procedure to assess the above problems and show that dataset quality can be enhanced with the aid of cluster analysis.

Genome sequence of Chrysodeixis chalcites nucleopolyhedrovirus, a baculovirus with two DNA photolyase genes

The complete genome sequence of a single nucleocapsid nucleopolyhedrovirus recently isolated from Chrysodeixis chalcites (ChchNPV) was determined. The viral genome has a size of 149 622 bp and an overall G+C content of 39.1 mol%. The sequence contains 151 predicted open reading frames (ORFs) with a minimal size of 50 codons. The similarity of these ORFs with those of other completely sequenced baculoviruses was calculated using a newly developed database, named GECCO. Phylogenetic analysis of the whole genome confirmed the evolutionary relationship of ChchNPV with group II NPVs, as did the absence of the NPV group I-specific gp64 gene. It is the first group II NPV to encode proliferating cell nuclear antigen. Most noteworthy is the presence of two ORFs encoding a class II cyclobutane pyrimidine dimer DNA photolyase. These two ORFs share only 45 % amino acid identity and have different promoter motifs. Twenty-two additional unique baculovirus genes were identified, including a gene encoding a novel putative RING finger protein with a possible homologue in poxviruses.