The Jackson Laboratory Senescence Tissue Mapping Center (JAX-Sen TMC) - Data Analysis Core
The Jackson Laboratory Senescence Tissue Mapping Center (JAX-Sen TMC) - Data Analysis Core
批准号:
10683393
负责人:
Sheng Li
金额:
$104.73万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-08-15 至 2026-07-31
关键词:
Adipose tissueAgeAgingAntibodiesAtlasesBenchmarkingBiologic CharacteristicBiologicalBiological MarkersCell AgingCell CommunicationCellsClassificationCollaborationsCommon Data ElementCommunitiesComputational BiologyComputer Vision SystemsDataData AnalysesData AnalyticsData Coordinating CenterData SetDevelopmentGenerationsGeneticGoalsHealthHeartHumanHypothalamic structureImageInbreedingIndividualKidneyLinear ModelsMapsMass Spectrum AnalysisMetadataModalityMolecularMouse StrainsMusNuclear RNAPancreasPathway AnalysisPlacentaPoliciesPopulationPreparationProceduresProcessProteomicsRLK5-associated protein phosphataseReproducibilityResolutionSamplingStandardizationTestingThe Jackson LaboratoryTissuesVisualizationagedanalysis pipelinecell typecohortcomputerized data processingdata integrationdata managementdata sharing networksdeep learningdesignimaging Segmentationmass spectrometric imagingnovel markeropen sourceprocess optimizationprospectiveresponsesenescencesingle nucleus RNA-sequencingsingle-cell RNA sequencingsynergismtissue mappingtooltranscriptometranscriptome sequencingtranscriptomics
中文摘要
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英文摘要
PROJECT SUMMARY/ABSTRACT DATA ANALYSIS CORE
The objective of the Data Analysis Core (DAC) of the JAX-Sen mouse Tissue Mapping Center (TMC) is to
construct biomarker datasets and molecular maps of cellular senescence in mice and deliver these data to the
SenNet Consortium Organization and Data Coordinating Center (CODCC). The Biological Analysis Core (BAC)
of JAX-Sen will generate high-resolution, high-content molecular data to characterize cellular senescence in
mouse kidney, adipose tissue, pancreas, placenta, heart and hypothalamus in aged, inbred and genetically
diverse mouse cohorts. From these data, the DAC will establish state-of-the-art workflows for data annotation,
curation, and analysis of transcriptomic, imaging, and imaging mass spectrometry (IMS) data to build cellular
senescence maps. The DAC will collaborate closely with the DAC of the human SenNet TMC at JAX and UConn
Health (KAPP-Sen TMC), other human and mouse TMCs and the CODCC to develop and implement Network-
wide standards for processing, analyzing and visualizing SenNet data. The JAX-Sen DAC will leverage
significant recent advances in deep learning and computer vision to define robust biomarkers of senescent cells
and map their tissue context. To achieve its goals, the JAX-Sen DAC will implement rigorous and reproducible
data annotation, curation, processing, and dissemination (Aim 1). The DAC will receive and centralize
sequencing, imaging, and IMS data from the JAX-Sen BAC. It will automate and harden QC procedures to screen
for annotation and curation errors, batch effects, and low-quality samples in collaboration with the BAC. The
DAC will implement the pipelines based on common community standards, benchmark on JAX-Sen and
reference datasets, and then containerize for sharing with the CODCC. From these data, the JAX-Sen DAC will
construct biomarker datasets and molecular maps of cellular senescence (Aim 2). The DAC will deploy analysis
pipelines for sequencing, image and IMS data with known and prospective senescence markers to identify and
functionally annotate novel biomarkers of senescent cells and map their tissue context, compute the diversity
within senescent cell populations, and quantify cell-to-cell interactions between senescent cells and neighboring
cells. The DAC will aggregate and integrate these data and metadata to build high-quality maps of cellular
senescence. Finally, the JAX-Sen DAC will disseminate JAX-Sen data with rigorous and reproducible open-
source processing pipelines (Aim 3). The DAC will harmonize, standardize, and disseminate data processing
and analytic pipelines with the CODCC, adhering to common community standards, standard operating
procedures, and the network data sharing policy to exact reproducibility. We will collaborate with KAPP-Sen and
other CODCC projects and TMCs to identify synergy, e.g., align human and mouse biomarkers on the same
tissues.
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