The function to process raw phenotype, genotype, covariates data across ancestries.

Parameters:

rawData: List[RawData]¶

Raw data for phenotypes, genotypes, covariates across ancestries.

keep_subject: List[str]¶

The DataFrame that contains subject ID that fine-mapping performs on.

pi: DataFrame¶

The DataFrame that contains prior weights for each SNP to be causal.

keep_ambiguous: bool¶

The indicator whether to keep ambiguous SNPs.

maf: float¶

The minor allele frequency threshold to filter the genotypes.

rint: bool¶

The indicator whether to perform rank inverse normalization on each phenotype data.

no_regress: bool¶

The indicator whether to regress genotypes on covariates.

mega: bool¶

The indicator whether to prepare datasets for mega SuShiE.

cv: bool¶

The indicator whether to prepare datasets for cross-validation.

cv_num: int¶

The number for \(X\)-fold cross-validation.

seed: int¶

The random seed for row-wise shuffling the datasets for cross validation.

Returns:

A tuple of

1. SNP information (pd.DataFrame),

2. dataset for running SuShiE (io.CleanData),

3. dataset for mega SuShiE (Optional[io.CleanData]),

4. dataset for cross-validation (Optional[List[io.CVData]]).

Return type:

Tuple[pd.DataFrame, io.CleanData, Optional[io.CleanData], Optional[List[io.CVData]]]