View source: R/merge_finemapping_results.R
merge_finemapping_results | R Documentation |
Gather fine-mapping results from echolocatoR across all loci and merge into a single data.frame.
merge_finemapping_results(
dataset = file.path(tempdir(), "Data/GWAS"),
minimum_support = 1,
include_leadSNPs = TRUE,
LD_reference = NULL,
save_path = tempfile(fileext = "merged_results.csv.gz"),
from_storage = TRUE,
credset_thresh = 0.95,
consensus_thresh = 2,
exclude_methods = NULL,
top_CS_only = FALSE,
verbose = TRUE,
nThread = 1
)
dataset |
Path to the folder you want to recursively search for results files within (e.g. "Data/GWAS/Nalls23andMe_2019"). Set this to a path that includes multiple subfolders if you want to gather results from multiple studies at once (e.g. "Data/GWAS"). |
minimum_support |
Filter SNPs by the minimum number of fine-mapping tools that contained the SNP in their Credible Set. |
include_leadSNPs |
Include lead GWAS/QTL SNPs per locus (regardless of other filtering criterion). |
LD_reference |
LD reference to use:
|
save_path |
Path to save merged table to. |
from_storage |
Search for stored results files. |
credset_thresh |
The minimum mean Posterior Probability (across all fine-mapping methods used) of SNPs to be included in the "mean.CS" column. |
consensus_thresh |
The minimum number of fine-mapping tools in which a SNP is in the Credible Set in order to be included in the "Consensus_SNP" column. |
exclude_methods |
Exclude certain fine-mapping methods when estimating mean.CS and Consensus_SNP. |
top_CS_only |
Only include the top 1 CS per fine-mapping method. |
verbose |
Print messages. |
nThread |
Number of threads to parallelise across. |
dataset <- get_Nalls2019_loci(return_dir = TRUE)
merged_DT <- merge_finemapping_results(dataset = dataset)
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