Multi-subject Single Cell Deconvolution
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Updated
Mar 4, 2024 - R
Multi-subject Single Cell Deconvolution
Find causal cell-types underlying complex trait genetics
An R package for performing association analysis of whole-genome/whole-exome sequencing (WGS/WES) studies using STAARpipeline
R package to perform Bayesian Genome-Wide Association Studies
An R package for performing MetaSTAAR procedure in whole-genome sequencing studies
A statistical test of pleiotropic effect of a genetic variant on two traits using GWAS summary statistics
The tutorial for performing association analysis of whole-genome/whole-exome sequencing (WGS/WES) studies using FAVORannotator, STAARpipeline and STAARpipelineSummary
metaUSAT is a data-adaptive statistical approach for testing genetic associations of multiple traits from single/multiple studies using univariate GWAS summary statistics.
Estimate genetic correlation using predicted expression
An R package for summarizing and visualizing association analysis results of whole-genome/whole-exome sequencing (WGS/WES) studies generated by STAARpipeline
Tools for regression using pre-computed summary statistics
An R package for performing MultiSTAAR procedure in whole-genome sequencing studies
Replication of an mQTL analysis using the ``locus'' method on simulated data
An app for performing association analysis of whole-genome/whole-exome sequencing (WGS/WES) studies using STAARpipeline in UK Biobank RAP
mvtests: a suite of functions for testing genetic associations of multiple traits (a.k.a. cross-phenotype associations)
Summary statistics-based association test for identifying the pleiotropic effects with set of genetic variants
Analysis of transcriptome imputation using paired genotype-expression data from SAGE and GEUVADIS
An app for summarizing association analysis results of whole-genome/whole-exome sequencing (WGS/WES) studies in UK Biobank RAP
USAT uses a data-adaptive weighted score-based test statistic for testing association of multiple continuous phenotypes with a single genetic marker.
A nonparametric statistics based method for hub and co-expression module identification in large gene co-expression network
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