Package: pleioh2g 0.1.3

Yujie Zhao

pleioh2g: Estimation of Pleiotropic Heritability from Genome-Wide Association Studies (GWAS) Summary Statistics

Provides tools to compute unbiased pleiotropic heritability estimates of complex diseases from genome-wide association studies (GWAS) summary statistics. We estimate pleiotropic heritability from GWAS summary statistics by estimating the proportion of variance explained from an estimated genetic correlation matrix (Bulik-Sullivan et al. 2015 <doi:10.1038/ng.3406>) and employing a Monte-Carlo bias correction procedure to account for sampling noise in genetic correlation estimates.

Authors:Yujie Zhao [aut, cre]

pleioh2g_0.1.3.tar.gz
pleioh2g_0.1.3.tar.gz(r-4.7-any)pleioh2g_0.1.3.tar.gz(r-4.6-any)
pleioh2g_0.1.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
pleioh2g/json (API)

# Install 'pleioh2g' in R:

install.packages('pleioh2g', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

h2_vector - H2 vector for 62 traits
h2_vector_mat - H2 jk matrix for 62 traits
Results_full_rg - Genetic correlation matrix for 62 traits
Results_full_rg_array - Jackknife array of genetic correlations
Rg_mat_z - Genetic correlation Z matrix for 62 traits

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.60 score 3 scripts 359 downloads 23 exports 34 dependencies

Last updated from:3f1b7cdc3c. Checks:4 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	144
source / vignettes	OK	254
linux-release-x86_64	OK	137
wasm-release	OK	125

Exports:Cal_cor_pleiotropic_h2 Cal_cor_pleiotropic_h2_corrected_single Cal_cor_pleiotropic_h2_single Cal_cor_test_single Cal_rg_h2g_alltraits Cal_rg_h2g_jk_alltraits generate_proposal_sample_changea_cor h2_liability ldsc_h2 ldsc_rg make_weights merge_sumstats perform_analysis pleiotropyh2_cor_computing_single pleiotropyh2_cor_computing_single_prune pleiotropyh2_nocor_computing_single Prune_disease_selection_DTrgzscore pruning_pleioh2g_wrapper read_ld read_m read_sumstats read_wld sumstats_munged_example_input

Dependencies:arrow assertthat backports bit bit64 checkmate cli cpp11 crayon data.table dplyr fs gdata generics glue gtools hms lifecycle magrittr mvtnorm pillar pkgconfig prettyunits progress purrr R6 rlang tibble tidyselect tzdb utf8 vctrs vroom withr

pleioh2g-tutorial

Installation: | Steps | Step 1: Prepare LDSC input-format data for multiple traits. | Step 2: Compute pleiotropic heritability with bias correction | Leave-category-out analysis instruction

Rendered frompleioh2g-tutorial.Rmdusingknitr::rmarkdown

Last update: 2025-10-28
Started: 2025-10-28

Help page	Topics
Compute a vector of pleioh2g for all diseases before correction This function computes pleioh2g for all diseases before correction in one go.	Cal_cor_pleiotropic_h2
Compute single pleioh2g for target disease after correction with referred disease index in the rg matrix and corrected ratio	Cal_cor_pleiotropic_h2_corrected_single
Compute single pleioh2g for target disease before correction with referred disease index in the rg matrix	Cal_cor_pleiotropic_h2_single
Compute inversed elements for the target disease in bias correction procedure with referred disease index in the rg matrix	Cal_cor_test_single
Compute rg + h2g	Cal_rg_h2g_alltraits
genomic-block jackknife and compute rg + h2g	Cal_rg_h2g_jk_alltraits
Generate samples based on sampling covariance matrix and rg matrix for target disease	generate_proposal_sample_changea_cor
Convert Heritability to Liability Scale	h2_liability
h2 vector for 62 traits	h2_vector
h2 jk matrix for 62 traits	h2_vector_mat
Estimate heritability - refer to ldscr R package (https://github.com/mglev1n/ldscr)	ldsc_h2
Estimate cross-trait genetic correlations (Robust Version) - refer to ldscr R package (https://github.com/mglev1n/ldscr)	ldsc_rg
Internal Function to make weights - refer to ldscr R package (https://github.com/mglev1n/ldscr)	make_weights
Merging summary statistics with LD-score files - refer to ldscr R package (https://github.com/mglev1n/ldscr)	merge_sumstats
Internal function to perform LDSC heritability/covariance analysis - refer to ldscr R package (https://github.com/mglev1n/ldscr)	perform_analysis
Compute pleioh2g after bias correction for target disease	pleiotropyh2_cor_computing_single
Compute pleioh2g after bias correction for target disease	pleiotropyh2_cor_computing_single_prune
Compute pleioh2g before bias correction for target disease	pleiotropyh2_nocor_computing_single
Prune disease selection	Prune_disease_selection_DTrgzscore
Perform pruning in computing pleioh2g and correct bias	pruning_pleioh2g_wrapper
Read ld from either internal or external file - refer to ldscr R package (https://github.com/mglev1n/ldscr)	read_ld
Read M from either internal or external file - refer to ldscr R package (https://github.com/mglev1n/ldscr)	read_m
Read summary statistics from either internal or external file - refer to ldscr R package (https://github.com/mglev1n/ldscr)	read_sumstats
Read wld from either internal or external file - refer to ldscr R package (https://github.com/mglev1n/ldscr)	read_wld
Genetic correlation matrix for 62 traits	Results_full_rg
Jackknife array of genetic correlations (62 traits)	Results_full_rg_array
Genetic correlation Z matrix for 62 traits	Rg_mat_z
Example munged dataframe - refer to ldscr R package (https://github.com/mglev1n/ldscr)	sumstats_munged_example_input

Package: pleioh2g 0.1.3

pleioh2g: Estimation of Pleiotropic Heritability from Genome-Wide Association Studies (GWAS) Summary Statistics

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)