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Multi-trait colocalization analysis pipeline

Source: R/colocboost_pipeline.R
colocboost_analysis_pipeline.Rd

This function perform a multi-trait colocalization using ColocBoost

Usage

colocboost_analysis_pipeline(
  region_data,
  focal_trait = NULL,
  event_filters = NULL,
  xqtl_coloc = TRUE,
  joint_gwas = FALSE,
  separate_gwas = FALSE,
  maf_cutoff = 5e-04,
  pip_cutoff_to_skip_ind = 0,
  remove_indels = FALSE,
  pip_cutoff_to_skip_sumstat = 0,
  qc_method = c("dentist", "slalom"),
  impute = TRUE,
  impute_opts = list(rcond = 0.01, R2_threshold = 0.6, minimum_ld = 5, lamb = 0.01),
  ...
)

Arguments

region_data

A region data loaded from load_regional_data.

focal_trait

Name of trait if perform focaled ColocBoost

event_filters

A list of pattern for filtering events based on context names. Example: for sQTL, list(type_pattern = ".*clu_(\d+_[+-?]).*",valid_pattern = "clu_(\d+_[+-?]):PR:",exclude_pattern = "clu_(\d+_[+-?]):IN:")

maf_cutoff

A scalar to remove variants with maf < maf_cutoff, dafault is 0.005.

pip_cutoff_to_skip_ind

A vector of cutoff values for skipping analysis based on PIP values for each context. Default is 0.

pip_cutoff_to_skip_sumstat

A vector of cutoff values for skipping analysis based on PIP values for each sumstat Default is 0.

qc_method

Quality control method to use. Options are "dentist" or "slalom" (default: "dentist").

impute

Logical; if TRUE, performs imputation for outliers identified in the analysis (default: TRUE).

impute_opts

A list of imputation options including rcond, R2_threshold, and minimum_ld (default: list(rcond = 0.01, R2_threshold = 0.6, minimum_ld = 5)).

Value

A list containing the individual_data and sumstat_data after QC: individual_data contains the following components if exist

  • Y: A list of residualized phenotype values for all tasks.

  • X: A list of residualized genotype matrices all tasks.

sumstat_data contains the following components if exist

  • sumstats: A list of summary statistics f or the matched LD_info, each sublist contains sumstats, n, var_y from load_rss_data.

  • LD_info: A list of LD information, each sublist contains combined_LD_variants, combined_LD_matrix, ref_panel load_LD_matrix.