Package index • functions

Mendelian Randomization

Functions for MR data formatting, harmonization, and analysis.

format_data(): Format Data for Mendelian Randomization Analysis
mr_leaveoneout_plot(): Plot results from leaveoneout analysis
mr_density_plot(): Density plot
mr_funnel_plot(): Funnel plot
mr_forest_plot(): Forest plot
mr_scatter_plot(): modification of TwoSampleMR mr_scatter_plot() function that adds exposure/outcome labels
calculate_r2(): calculate r2
calculate_fstat_from_r2(): calculate fstat from r2
calculate_fstat_from_beta_se(): calculate fstat from beta se
directional_consistency(): Workout consistency of effect estimates
alignment_check(): check the alignment of GWAS to reference panel and flip allele beta where required

Utilities for colocalization analysis and sensitivity checks.

coloc_check_alignment(): Check Alignment for Colocalisation
coloc_sensitivity(): Plots sensitivity analysis for coloc results
coloc_prior.adjust(): Adjust Colocalisation Prior Probabilities
coloc_prior.snp2hyp(): Convert SNP Prior to Hypotheses
coloc_manh.plot(): Plot Manhattan Plot for Colocalisation
coloc_plot_dataset(): plot a coloc dataset
finemap_pval_LD(): Perform LD clumping on a dataframe based on p-value threshold
finimom_cs_table(): Create a Table of Credible Sets from Finimom Model
susieR_cs_table(): Create a Table of Credible Sets from SusieR Model

Plotting functions for GWAS results and regional associations.

manhattan(): Creates a Manhattan plot
qqplot(): qqplot
miamiplot(): Create a Miami plot with a central buffer and fixed axis labels
gg_regionplot(): Create a Region Plot with Genetic Data and Recombination Rates
gg_locusplot(): Create a regional association plot The code is adapted from the locusplotr package.
forestplot(): forestplot function
blank_plot(): Create a blank ggplot2 plot
calculate_and_insert_percent_change(): Percent Change and Insertion

Utilities for integrating with the locuscomparer package.

General purpose functions and variant search utilities.

read_file(): Read File Based on Extension
remove_duplicate_SNP(): Remove duplicate rows based on SNP column
remove_nearby_positions(): Remove rows with nearby positions (excluding "cis" and "cis-trans_cis")
biomaRt_getBM_batch(): Retrieve Batched Data from BioMart with Filters and Attribute Chunks
get_ld_proxies(): Find LD proxies for a set of SNPs
proxy_search(): proxy_search: search for proxies when using read_outcome_data()
proxy_search_DECODE(): finds proxy SNPs from an internal reference (DECODE format)
proxy_search_UKB(): finds proxy SNPs from an internal reference (UKB format)
proxy_search_split(): finds proxy SNPs from an internal reference split the SNP search into 10k blocks
missing_EAF(): Fill Missing EAF Values in Data Frame
replace_na_with_mean(): add the mean sample size for missing SNP sample sizes
model_test(): Provide akaike information criterion for all possible covariate combinations
palette(): make colour palettes
create_ids(): Create IDs from a vector of names
random_string(): Generate random strings