0000000000724816

AUTHOR

Manfred Schimmler

showing 4 related works from this author

Combining GPU and FPGA technology for efficient exhaustive interaction analysis in GWAS

2016

Interaction between genes has become a major topic in quantitative genetics. It is believed that these interactions play a significant role in genetic variations causing complex diseases. Due to the number of tests required for an exhaustive search in genome-wide association studies (GWAS), a large amount of computational power is required. In this paper, we present a hybrid architecture consisting of tightly interconnected CPUs, GPUs and FPGAs and a fine-tuned software suite to outperform other implementations in pairwise interaction analysis while consuming less than 300Watts and fitting into a standard desktop computer case.

0301 basic medicine03 medical and health sciences030104 developmental biologySoftware suiteComputer architecturePairwise interactionComputer scienceBrute-force searchGenome-wide association studyParallel computingComputer caseField-programmable gate arrayImplementation2016 IEEE 27th International Conference on Application-specific Systems, Architectures and Processors (ASAP)
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High-speed exhaustive 3-locus interaction epistasis analysis on FPGAs

2015

Abstract Epistasis, the interaction between genes, has become a major topic in molecular and quantitative genetics. It is believed that these interactions play a significant role in genetic variations causing complex diseases. Several algorithms have been employed to detect pairwise interactions in genome-wide association studies (GWAS) but revealing higher order interactions remains a computationally challenging task. State of the art tools are not able to perform exhaustive search for all three-locus interactions in reasonable time even for relatively small input datasets. In this paper we present how a hardware-assisted design can solve this problem and provide fast, efficient and exhaus…

General Computer ScienceComputer sciencebusiness.industryEpistasis and functional genomicsBrute-force searchGenome-wide association studyMutual informationQuantitative geneticsMachine learningcomputer.software_genreSupercomputerTheoretical Computer ScienceModeling and SimulationEpistasisPairwise comparisonArtificial intelligencebusinesscomputerJournal of Computational Science
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Parallelizing Epistasis Detection in GWAS on FPGA and GPU-Accelerated Computing Systems

2015

This is a post-peer-review, pre-copyedit version of an article published in IEEE - ACM Transactions on Computational Biology and Bioinformatics. The final authenticated version is available online at: http://dx.doi.org/10.1109/TCBB.2015.2389958 [Abstract] High-throughput genotyping technologies (such as SNP-arrays) allow the rapid collection of up to a few million genetic markers of an individual. Detecting epistasis (based on 2-SNP interactions) in Genome-Wide Association Studies is an important but time consuming operation since statistical computations have to be performed for each pair of measured markers. Computational methods to detect epistasis therefore suffer from prohibitively lon…

Computer scienceBioinformaticsDNA Mutational AnalysisGenome-wide association studyParallel computingPolymorphism Single NucleotideSensitivity and SpecificityComputational biologyComputer GraphicsGeneticsComputer architectureField-programmable gate arrayRandom access memoryApplied MathematicsChromosome MappingHigh-Throughput Nucleotide SequencingReproducibility of ResultsField programmable gate arraysEpistasis GeneticSignal Processing Computer-AssistedEquipment DesignRandom access memoryComputing systemsReconfigurable computingEquipment Failure AnalysisTask (computing)EpistasisHost (network)Graphics processing unitsGenome-Wide Association StudyBiotechnology
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FPGA-based Acceleration of Detecting Statistical Epistasis in GWAS

2014

Abstract Genotype-by-genotype interactions (epistasis) are believed to be a significant source of unexplained genetic variation causing complex chronic diseases but have been ignored in genome-wide association studies (GWAS) due to the computational burden of analysis. In this work we show how to benefit from FPGA technology for highly parallel creation of contingency tables in a systolic chain with a subsequent statistical test. We present the implementation for the FPGA-based hardware platform RIVYERA S6-LX150 containing 128 Xilinx Spartan6-LX150 FPGAs. For performance evaluation we compare against the method iLOCi[9]. iLOCi claims to outperform other available tools in terms of accuracy.…

epistasis020203 distributed computing0303 health sciencesXeonWorkstationComputer scienceGenome-wide association study02 engineering and technologycomputer.software_genrelaw.inventioncontingency tables03 medical and health sciencesAccelerationFPGA technologylaw0202 electrical engineering electronic engineering information engineeringGeneral Earth and Planetary SciencesEpistasisGWASData miningpairwise gene-gene interactionField-programmable gate arraycomputer030304 developmental biologyGeneral Environmental ScienceProcedia Computer Science
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