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Statistical Methods for Rare-Variant Sequencing Studies in
Pedigrees
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Novel Statistical Methods for Analyzing Next Generation Sequencing
Data
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Powerful variance-component method for TWAS identifies novel and known risk genes for Alzheimer’s dementia
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Applying Genome-Wide Association Study to Analyze Novel Variants That Potentially Relate to Alzheimer’s Disease
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Genome-wide DNA methylation profile change in cancer cell lines under stresses
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Analysis of age, tumor-sidedness, and mismatch repair (MMR) gene with response to immune checkpoint inhibitors (ICIs) in MMR-deficient (dMMR) colorectal cancer (CRC) patients (pts): A multi-institutional study
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EDClust: An EM-MM hybrid method for cell clustering in population-level single cell RNA sequencing
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Cell-type specific alteration of DNA methylation in Alzheimer’s Disease
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Gain of Chromosome 1q is Associated with Early Progression in Multiple Myeloma Patients Treated with Lenalidomide, Bortezomib, and Dexamethasone
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Bayesian Functional Genome-wide Association Study using Standardized Individual-level and Summary-level GWAS Data
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Integrate Proteomics Data with GWAS Summary data for Studying Alzheimer’s Disease by Nonparametric Bayesian Method
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TIGAR-V2 with nonparametric Bayesian eQTL weights estimated from GTEx V8 & Leveraging multiple reference panels to improve TWAS power by ensemble machine learning
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Potential biomarkers for ALS/FTD as a consequence of TDP-43 loss of function
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A benchmark of rare cell type detection methods for single-cell RNA sequencing data
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Exploring the Genetics and Biological Pathways of Obesity through Computational Biology and Statistical Approaches
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Genome-wide TWAS of brain and blood tissues identifies novel risk genes for Alzheimer’s disease dementia
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