Integrative genomic and epigenomic analysis of cancer using long read sequencing
使用长读长测序对癌症进行综合基因组和表观基因组分析
基本信息
- 批准号:10396074
- 负责人:
- 金额:$ 35.67万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-05-01 至 2024-04-30
- 项目状态:已结题
- 来源:
- 关键词:AccountingAddressAlgorithmic AnalysisAlgorithmsAllelesAutomobile DrivingBasic ScienceBioinformaticsBiological SciencesCancer BiologyCancerousCatalogingCharacteristicsClinicalCommunitiesComplexComputing MethodologiesCopy Number PolymorphismCytosineDNA Sequence RearrangementDNA Transposable ElementsDataData SetDetectionDevelopmentDiagnosticDiseaseEnsureEpigenetic ProcessGene Expression ProfilingGenerationsGenesGeneticGenetic VariationGenetic studyGenomeGenomicsGenotypeGoalsGraphGrowthHealthIndividualJointsKaryotypeMachine LearningMalignant NeoplasmsMediatingMethodsMethylationMinisatellite RepeatsModelingMonitorMosaicismMutationNatureNormal tissue morphologyOncogenesOutcomePathogenicityPatientsPhasePopulationProtein IsoformsRecurrenceRepetitive SequenceResearchResearch PersonnelResolutionResourcesRoleSample SizeSamplingSignal TransductionSomatic MutationStatistical MethodsStructureSystemTandem Repeat SequencesTechnologyTissuesTumor Suppressor ProteinsVariantWorkbasecancer genomecancer genomicscancer initiationcancer riskcancer therapycancer typecohortdisorder riskdriver mutationepigenetic profilingepigenetic variationepigenomeepigenomicsexperiencefusion genegenetic pedigreegenetic variantgenome analysisgenome sequencingimprovedindexinginsightinstrumentmethylomenanoporenovelnovel strategiesopen sourcepower analysispremalignantprognostic indicatorrisk variantsequencing platformsingle moleculetranscriptometranscriptomicstumortumor heterogeneitytumor progression
项目摘要
PROJECT SUMMARY
The last twenty years have experienced extensive growth in the sequencing of cancer genomes, leading to a
dramatically increased understanding of the role of genetic and epigenetic mutations in cancer. This has largely
been enabled by developments in high-throughput “second-generation” sequencing technology and analysis
that characterize cancer genomes using short-reads. Recently, a new generation of high-throughput long-read
sequencing instruments, primarily from Pacific Biosciences and Oxford Nanopore, have become available that
are poised to displace short-read sequencing for many applications. We and others have used these
technologies to discover tens of thousands of variants per cancer genome that are not detectable using
short-reads, including structural variants and differentially methylated regions in known oncogenes and cancer
risk genes. These technologies carry the potential to address many open questions in cancer biology, however,
the analysis of long-read sequencing data is computationally demanding and needs specialized algorithms that
are either too inefficient to use at scale or do not yet exist. In this proposal, we will address several gaps in the
application of long-read technology for basic research and clinical use in cancer genomics. First, we will
develop improved methods for finding structural variants and complex repeat expansions from long-reads,
both of which are major diagnostic and prognostic indicators of disease, yet are not accurately identified using
existing methods. Leveraging the improved phasing capabilities of long reads, this work will include the
detection of mosaic variants, revealing tumor heterogeneity and variants in precancerous tissues. Next, we will
apply machine learning and systems level advances to accelerate and improve the comparison of variants
across large patient cohorts. Critically, this will compensate for the error prone nature of single molecule
long-read sequencing to make these comparisons more accurate when comparing tumor-normal samples or
pedigrees of related patients so that recurrent driving mutations can be accurately identified. Finally, we will
develop integrative methods for the joint analysis of genome, transcriptome, and epigenetic profiling of cancer
genomes. These advances will improve the identification of fusion genes, and allow for entirely new forms of
epigenetic analysis, such as the allele-specific analysis of methylation across transposable elements and other
repetitive elements. Synthesizing the many thousands of novel variants we will detect using our methods, we
will then develop algorithms that will identify and evaluate recurrent genetic or epigenetic variations as
putative driving mutations. All methods will be released open-source and will empower us, our ITCR
collaborators, and the cancer genomics community at large to study genetic and epigenetic variants with near
perfect accuracy and thereby unlock many new associations to treatment and disease.
项目总结
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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MICHAEL SCHATZ其他文献
MICHAEL SCHATZ的其他文献
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{{ truncateString('MICHAEL SCHATZ', 18)}}的其他基金
EXPANDING THE GENOMIC DATA SCIENCE COMMUNITY NETWORK FOR NHGRI.
扩大 NHGRI 的基因组数据科学社区网络。
- 批准号:
10944109 - 财政年份:2023
- 资助金额:
$ 35.67万 - 项目类别:
Optimized workflows for structural variant analysis of the Kids First genomes using short and long reads
使用短读长和长读长对 Kids First 基因组进行结构变异分析的优化工作流程
- 批准号:
10432507 - 财政年份:2022
- 资助金额:
$ 35.67万 - 项目类别:
Optimized workflows for structural variant analysis of the Kids First genomes using short and long reads
使用短读长和长读长对 Kids First 基因组进行结构变异分析的优化工作流程
- 批准号:
10602532 - 财政年份:2022
- 资助金额:
$ 35.67万 - 项目类别:
Integrative genomic and epigenomic analysis of cancer using long read sequencing
使用长读长测序对癌症进行综合基因组和表观基因组分析
- 批准号:
10599150 - 财政年份:2021
- 资助金额:
$ 35.67万 - 项目类别:
Integrative genomic and epigenomic analysis of cancer using long read sequencing
使用长读长测序对癌症进行综合基因组和表观基因组分析
- 批准号:
10187808 - 财政年份:2021
- 资助金额:
$ 35.67万 - 项目类别:
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