Lamatz: Compute the list of significant SNPs using the GWAS summary...
In baolinwu/MTAR: Various Multi-Trait Association tests in R
Description
Usage
Arguments
Value
References
Description
We compute the significant SNPs for the adaptive test (AZ) based on weighting the SZ and SZ2 tests.
Usage
1
Lamatz(Z, Sig, rho = 0:10/10, alpha = 5e-08)
Arguments
Z
matrix of summary Z-statistics (SNPs by traits)
Sig
the estimated marginal trait correlation matrix
rho
weights for the SZ
alpha
desired genome-wide significance level (default to 5E-8)
Value
- idAZ
significant SNP list for AZ
References
Guo,B. and Wu,B. (2018) Integrate multiple traits to detect novel disease-gene association using GWAS summary data with an adaptive test approach. Bioinformatics, under revision.
baolinwu/MTAR documentation built on May 14, 2019, 6:03 a.m.
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Description Usage Arguments Value References
Description
We compute the significant SNPs for the adaptive test (AZ) based on weighting the SZ and SZ2 tests.
Usage
1 | Lamatz(Z, Sig, rho = 0:10/10, alpha = 5e-08)
|
Arguments
Z |
matrix of summary Z-statistics (SNPs by traits) |
Sig |
the estimated marginal trait correlation matrix |
rho |
weights for the SZ |
alpha |
desired genome-wide significance level (default to 5E-8) |
Value
- idAZ
significant SNP list for AZ
References
Guo,B. and Wu,B. (2018) Integrate multiple traits to detect novel disease-gene association using GWAS summary data with an adaptive test approach. Bioinformatics, under revision.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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