Dataset Information

High-throughput bioinformatics with the Cyrille2 pipeline system.

ABSTRACT:

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.

SUBMITTER: Fiers MW

PROVIDER: S-EPMC2268656 | biostudies-literature | 2008 Feb

REPOSITORIES: biostudies-literature

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Publications

High-throughput bioinformatics with the Cyrille2 pipeline system.

Fiers Mark W E J MW van der Burgt Ate A Datema Erwin E de Groot Joost C W JC van Ham Roeland C H J RC

BMC bioinformatics 20080212

<h4>Background</h4>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 pipelin ...[more]

PMID: 18269742

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Project description:BackgroundSingle nucleotide polymorphisms (SNPs) as defined here are single base sequence changes or short insertion/deletions between or within individuals of a given species. As a result of their abundance and the availability of high throughput analysis technologies SNP markers have begun to replace other traditional markers such as restriction fragment length polymorphisms (RFLPs), amplified fragment length polymorphisms (AFLPs) and simple sequence repeats (SSRs or microsatellite) markers for fine mapping and association studies in several species. For SNP discovery from chromatogram data, several bioinformatics programs have to be combined to generate an analysis pipeline. Results have to be stored in a relational database to facilitate interrogation through queries or to generate data for further analyses such as determination of linkage disequilibrium and identification of common haplotypes. Although these tasks are routinely performed by several groups, an integrated open source SNP discovery pipeline that can be easily adapted by new groups interested in SNP marker development is currently unavailable.ResultsWe developed SNP-PHAGE (SNP discovery Pipeline with additional features for identification of common haplotypes within a sequence tagged site (Haplotype Analysis) and GenBank (-dbSNP) submissions. This tool was applied for analyzing sequence traces from diverse soybean genotypes to discover over 10,000 SNPs. This package was developed on UNIX/Linux platform, written in Perl and uses a MySQL database. Scripts to generate a user-friendly web interface are also provided with common queries for preliminary data analysis. A machine learning tool developed by this group for increasing the efficiency of SNP discovery is integrated as a part of this package as an optional feature. The SNP-PHAGE package is being made available open source at http://bfgl.anri.barc.usda.gov/ML/snp-phage/.ConclusionSNP-PHAGE provides a bioinformatics solution for high throughput SNP discovery, identification of common haplotypes within an amplicon, and GenBank (dbSNP) submissions. SNP selection and visualization are aided through a user-friendly web interface. This tool is useful for analyzing sequence tagged sites (STSs) of genomic sequences, and this software can serve as a starting point for groups interested in developing SNP markers.

Dataset Information

High-throughput bioinformatics with the Cyrille2 pipeline system.

Background

Results

Conclusion

Publications

High-throughput bioinformatics with the Cyrille2 pipeline system.

Similar Datasets

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