laijiang
. See also theR-universe documentation.Package: CIVMR 0.0.1
CIVMR: Constrained Instrumental Variables in Mendelian Randomization with Pleiotropy
In Mendelian randomization (MR), genetic variants are used to construct instrumental variables that then enable inference about the causal relationship between a phenotype of interest and a response or disease outcome. However, valid MR inference requires several assumptions, including the assumption that the genetic variants only influence the response through the phenotype of interest.Pleiotropy occurs when a genetic variant has an effect on more than one different phenotypes, and therefore a pleiotropic genetic variant may be an invalid instrumental variable.Hence, a naive method for constructing an instrumental variables may lead to biased estimation of the association between the phenotype and the response. Here, we encode a new and intuitive method (Constrained Instrumental Variable method [CIV]) to construct valid instrumental variables and perform adjusted causal effect estimation when pleiotropic exists, focusing particularly on the situation where pleiotropic phenotypes have been measured. Our approach is theoretically guaranteed to perform an automatic and valid selection of genetic variants when building the instrumental variable. We also provide details of the features of many existing methods, together with a comparison of their performance in a large series of simulations. CIV performs robustly across many different pleiotropic violations of the MR assumptions.
Authors:
CIVMR_0.0.1.tar.gz
CIVMR_0.0.1.zip(r-4.5)CIVMR_0.0.1.zip(r-4.4)CIVMR_0.0.1.zip(r-4.3)
CIVMR_0.0.1.tgz(r-4.4-any)CIVMR_0.0.1.tgz(r-4.3-any)
CIVMR_0.0.1.tar.gz(r-4.5-noble)CIVMR_0.0.1.tar.gz(r-4.4-noble)
CIVMR_0.0.1.tgz(r-4.4-emscripten)CIVMR_0.0.1.tgz(r-4.3-emscripten)
CIVMR.pdf |CIVMR.html✨
CIVMR/json (API)
# Install 'CIVMR' in R: |
install.packages('CIVMR', repos = c('https://mrcieu.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/laijiang/civmr/issues
- ADNI - ADNI Data.
- simulation - Simulation Data.
Last updated 4 years agofrom:972613ed33. Checks:ERROR: 7. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | FAIL | Dec 03 2024 |
R-4.5-win | ERROR | Dec 03 2024 |
R-4.5-linux | ERROR | Dec 03 2024 |
R-4.4-win | ERROR | Dec 03 2024 |
R-4.4-mac | ERROR | Dec 03 2024 |
R-4.3-win | ERROR | Dec 03 2024 |
R-4.3-mac | ERROR | Dec 03 2024 |
Exports:alleleboot_CIVCIVcv_CIVIV_reductionLA_decompositionlmplmPvaluepcc_IVrm_outlier_IVsmooth_CIVsmooth_L0_lambdaSNP_reductionsolve_pccTSLS_IV
Dependencies:
Readme and manuals
Help Manual
Help page | Topics |
---|---|
ADNI Data. | ADNI |
cross-validated Allele score method. | allele |
bootstrapped CIV (recommended). | boot_CIV |
Find a unique solution of CIV. | CIV |
cross-validated CIV. | cv_CIV |
Instrumental variable reduction. | IV_reduction |
linear algebra decompositions for CIV. (internal function.) | LA_decomposition |
simple linear regression pvalues (internal function.) | lmp |
univariate T-test p-values. | lmPvalue |
multiple orthogonal CIV solutions. (internal function) | pcc_IV |
select IVs from a smooth_IV object (experimental function). | rm_outlier_IV |
simulation Data. | simulation |
CIV_smooth solution with cross-validation.(recommended) | smooth_CIV |
CIV_smooth solution given lambda. (Internal function) | smooth_L0_lambda |
SNP pre-processing. | SNP_reduction |
Find a unique solution of CIV (internal use). | solve_pcc |
Two stage least square method. | TSLS_IV |