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Table 1 Overview of the analyzed sample and data in the contributions

From: Joint analysis of multiple phenotypes: summary of results and discussions from the Genetic Analysis Workshop 19

Ref. #

Contribution

Sample

BP data

GE and genetic data

Method

Software

Main findings

[8]

Cao et al. [2015]

n = 397 individuals in 46 families, from family data set

Real data: SBP at time point 3

GE and SNP data: k = 11,522 transcripts, l = 354,893 SNPs

SRVS

Matlab-toolbox SRVS

Of top 1000 variables associated with BP, 575 are SNPs and 425 are GE, 302 have plausible relevance for BP, 173 are associated with body weight, and 84 associated with left ventricular contractility

[9]

Konigorski et al. [2015]

n = 81 unrelated individuals, from family data set

Real data: SBP at time point 1

GE and WGS data on chromosome 19: k = 848 transcripts, l = 68,727 SNVs

Copula

R functions, available upon request

Higher power of bivariate copula models compared to univariate regression and univariate SKAT, SKAT-O

Identification of 5 SNVs in CEACAM5 gene relevant for SBP, and 1075 cis-eQTLs relevant for GE

[10]

Song et al. [2015]

n = 1389 individuals from family data set

Real data: SBP and DBP at time points 1–3

SNP data: l = 460,359 SNPs

SEM

R-package strum

The 2 tested models (autoregressive and latent growth curve) show similar ranking of relevant SNPs

Identification of 10 SNPs related to both SBP and DBP, mostly on chromosome 1

[11]

Sun et al. [2015]

n = 1851 unrelated individuals, from unrelated data set

real data: SBP and DBP

WES data: l = 152,337 SNVs

MURAT

R functions, available upon request

Multivariate tests tend to give smaller p values than the univariate SKAT, and can improve power

Identification of 2 SNPs in CYP4A22 and near APOC4, which were previously reported to be associated with BP

  1. BP blood pressure, eQTL expression quantitative trait locus, GE gene expression, MURAT multivariate rare-variant association test, SBP/DBP systolic/diastolic blood pressure, SEM structural equation modeling, SKAT sequence kernel association test, SKAT-O optimal sequence kernel association test, SNP single nucleotide polymorphism, SNV single nucleotide variant, SRVS sparse representation variable selection, WES whole exome sequence, WGS whole genome sequence