check_miss_data: Remove SNPs with missing data

In neurogenomics/MungeSumstats: Standardise summary statistics from GWAS

Remove SNPs with missing data

Description

Remove SNPs with missing data

Usage

check_miss_data(
  sumstats_dt,
  path,
  log_folder_ind,
  check_save_out,
  tabix_index,
  nThread,
  log_files,
  drop_na_cols
)

Arguments

path	Filepath for the summary statistics file to be formatted. A dataframe or datatable of the summary statistics file can also be passed directly to MungeSumstats using the path parameter.
log_folder_ind	Binary Should log files be stored containing all filtered out SNPs (separate file per filter). The data is outputted in the same format specified for the resulting sumstats file. The only exception to this rule is if output is vcf, then log file saved as .tsv.gz. Default is FALSE.
tabix_index	Index the formatted summary statistics with tabix for fast querying.
nThread	Number of threads to use for parallel processes.
log_files	list of log file locations
drop_na_cols	A character vector of column names to be checked for missing values. Rows with missing values in any of these columns (if present in the dataset) will be dropped. If NULL, all columns will be checked for missing values. Default columns are SNP, chromosome, position, allele 1, allele2, effect columns (frequency, beta, Z-score, standard error, log odds, signed sumstats, odds ratio), p value and N columns.

Value

list containing sumstats_dt, the modified summary statistics data table object and a log file list.

neurogenomics/MungeSumstats documentation built on May 2, 2024, 9:04 a.m.