Accelerating genomic analysis for time critical clinical applications
Accelerating genomic analysis for time critical clinical applications
批准号:
10593480
负责人:
Gabor T Marth
金额:
$21.56万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
已结题
起止时间:
2023-01-10 至 2024-12-31
关键词:
AccelerationAdoptedAdoptionAdvanced Malignant NeoplasmAlgorithmic AnalysisAlgorithmsAreaArtificial IntelligenceBioinformaticsBiopsyCancer PatientCharacteristicsChildhoodClinicClinicalCodeCollaborationsCollectionCommunitiesComputer softwareConsumptionCritically ill childrenDNA sequencingDataData AnalysesData SetDemocracyDevelopmentDiagnosticDropsExclusionFunding OpportunitiesFutureGenerationsGenomeGenomicsGerm-Line MutationGoalsHourHuman GenomeInformaticsLaboratoriesLibrariesManualsMathematicsMeasuresModalityMutation DetectionNeonatal Intensive Care UnitsPatientsPerformancePositioning AttributeProcessResearchSelection for TreatmentsSequence AlignmentSomatic MutationSpeedTechniquesTimeVariantWorkanalysis pipelinebasecancer therapyclinical applicationclinically relevantcomputerized data processingcostdesignexperiencegenome sequencinggenome-widegigabyteinformatics toolmodel developmentnext generation sequencingopen sourceoptimal treatmentsparallelizationprecision medicineprecision oncologyprogramssuccesstask analysistooltumorwhole genome
中文摘要
点击翻译按钮获取中文摘要
英文摘要
SUMMARY / ABSTRACT
Genome-scale DNA sequencing has revolutionized the practice of precision medicine, at dramatically reduced
cost. It is possible today to sequence an entire human genome in roughly one day; however, bioinformatic
analysis typically takes days or weeks, and has emerged as the major bottleneck for successfully utilizing
genome sequencing in time-critical applications, e.g. for identifying the genomic vulnerabilities of a patient’s
tumor for rational cancer treatment selection within a clinically relevant timeframe. The overarching goal of this
proposal is to dramatically speed up genomic analysis algorithms via heterogeneous computing
techniques. Here we will focus on one critical aspect of genomic analysis, i.e. variant calling, and set the
ambitious goal of completing the analysis of a 60X-coverage Illumina whole genome sequencing dataset in under
10 minutes, far faster than the current state of the art. Although here applied to only one analysis task,
accomplishing such a high degree of acceleration would demonstrate that the techniques we are developing in
this proposal are also generalizable across many other genomic analysis tasks. Our approach is to first
accelerate the most widely reusable software components, to maximize value for the genomic analysis tool
developer community, who will then be able to integrate these components into their own tools.
With these reusable software components, we will accelerate the FreeBayes variant caller tool. FreeBayes is a
widely used germline variant and somatic mutation detection tool, and therefore acceleration will benefit a large
user audience. This software was developed in our own laboratory, and therefore we are intimately familiar with
its algorithms and code base, positioning us for success in this exploratory project. If successful, our technique
will be applicable for accelerating many, currently time-consuming analysis tasks. As a result, analysts will be
able to finish sophisticated data processing tasks within minutes, as part of their interactive analysis session
rather than a batched background process, and complete manual result review immediately after; rendering the
complete analysis process sufficiently fast for time-critical clinical applications.
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Data Management Core
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Cardiovascular Development Data Resource Center (CDDRC)
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Cardiovascular Development Data Resource Center (CDDRC)
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Longitudinal models of breast cancer for studying mechanisms of therapy response and resistance
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IOBIO: Web-based, interactive tools for real-time analysis in genomic big data
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依托单位:
Bioinformatics Core
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财政年份:2017
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Web tools for physician-driven diagnostic interpretation of genomic patient data
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Adapting Functional Precision Oncology for pediatric brain cancer
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Monitoring tumor subclonal heterogeneity over time and space
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Monitoring tumor subclonal heterogeneity over time and space
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财政年份:2016
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Monitoring tumor subclonal heterogeneity over time and space
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Empowering real-time, web-based genomic big data analysis at commercial scale.
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依托单位:
海外基金