Homeworks for statistic genetics
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Updated
Jan 15, 2018 - HTML
Homeworks for statistic genetics
Estimate genetic correlation using predicted expression
Routine computations in regression
exploration of TreeWas/TreeWas2 code for the Zaitlen lab. Based on TreeWas developed by McVean Lab @ Oxford.
Replication of an mQTL analysis using the ``locus'' method on simulated data
A nonparametric statistics based method for hub and co-expression module identification in large gene co-expression network
USAT uses a data-adaptive weighted score-based test statistic for testing association of multiple continuous phenotypes with a single genetic marker.
POM-PS tests for genetic associations of secondary traits from case-control GWAS.
Analysis of transcriptome imputation using paired genotype-expression data from SAGE and GEUVADIS
Assumptions about frequency-dependent architectures of complex traits bias measures of functional enrichment
Julia implementation of Factored Spectrally Transformed Linear Mixed Models
metaUSAT is a data-adaptive statistical approach for testing genetic associations of multiple traits from single/multiple studies using univariate GWAS summary statistics.
GEAR [GEnetic Analysis Repository], contact chenguobo@gmail.com;
The Peaks software GitHub repository
A statistical test of pleiotropic effect of a genetic variant on two traits using GWAS summary statistics
mvtests: a suite of functions for testing genetic associations of multiple traits (a.k.a. cross-phenotype associations)
Joint meta-analysis of 2-df gene and gene-environment tests in GWAS.
Multi Kernel Linear Mixed Models for Complex Phenotype Prediction
Association testing of bisulfite sequencing methylation data via a Laplace approximation
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