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A fast and robust strategy to remove variant level artifacts in Alzheimer’s Disease Sequencing Project data (Belloy et al. 2022) (via DSS) |
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A longitudinal study of Alzheimer Disease and other dementing illnesses – KnightADRC GWAS (via DSS) |
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ACT and Genetic Differences GWAS |
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535539 |
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ADC1- Alzheimer Disease Center Dataset 1 (via DSS) |
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520345 |
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ADC2- Alzheimer Disease Center Dataset 2 (via DSS) |
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525723 |
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ADC3- Alzheimer Disease Center Dataset 3 (via DSS) |
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659224 |
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ADC4 - Alzheimer Disease Center Dataset 4 (via DSS) |
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639151 |
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ADC5 - Alzheimer Disease Center Dataset 5 (via DSS) |
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637167 |
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ADC6 - Alzheimer Disease Center Dataset 6 (via DSS) |
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635372 |
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ADC7 - Alzheimer Disease Center Dataset 7 (via DSS) |
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628661 |
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ADGC African American Summary Statistics- Reitz et al. (2013) |
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ADGC Age at Onset Summary Statistics- Naj et al. (2014) |
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ADGC case-control summary statistics on 7050 samples not included in the IGAP-2013 discovery stage- Hu et al. (2019) |
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ADGC Neuropath Summary Stats and Phenotypes- Beecham et al. (2014) |
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ADGC Summary Statistics- Naj et al. (2011) |
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Caribbean Hispanic AD Study |
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166 |
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CHOP Exome Chip |
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241547 |
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CLU, A potential endophenotype for AD: Summary Statistics- Deming et al. (2016) |
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CSF Aβ/ptau Summary Statistics - Deming Y et al. (2017) |
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CSF Summary Statistics- Cruchaga et al. (2013) |
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