MetaSTAAR_cond: Meta-analysis of STAAR (MetaSTAAR) procedure for conditional...

In xihaoli/MetaSTAAR: Meta-Analysis of STAAR (MetaSTAAR) Procedure for Dynamic Incorporation of Multiple Functional Annotations in Whole Genome Sequencing Studies

Meta-analysis of STAAR (MetaSTAAR) procedure for conditional analysis using omnibus test

Description

The MetaSTAAR_cond function takes in the object from the merged conditional summary statistics and covariance files of each participating study and functional annotation data to analyze the conditional association between a quantitative/dichotomous phenotype and a variant-set by using the meta-analysis of STAAR (MetaSTAAR) procedure, adjusting for a given list of variants. For each variant-set, the MetaSTAAR-O p-value is a p-value from an omnibus test that aggregated conditional SKAT-MS(1,25), SKAT-MS(1,1), Burden-MS(1,25), Burden-MS(1,1), ACAT-V-MS(1,25), and ACAT-V-MS(1,1) together with conditional p-values of each test weighted by each annotation using Cauchy method.

Usage

MetaSTAAR_cond(
  obj_MetaSTAAR_merge_cond,
  annotation_phred = NULL,
  rv_num_cutoff = 2
)

Arguments

obj_MetaSTAAR_merge_cond	an object from merging the conditional summary statistics and covariance files from each participating study, adjusting for a given list of variants, which is the output from MetaSTAAR_merge_cond.
annotation_phred	a data frame or matrix of functional annotation data of dimension p*q (or a vector of a single annotation score with length p), where p is the number of genetic variants in the variant-set. Continuous scores should be given in PHRED score scale, where the PHRED score of j-th variant is defined to be -10*log10(rank(-score_j)/total) across the genome. (Binary) categorical scores should be taking values 0 or 1, where 1 is functional and 0 is non-functional. If not provided, MetaSTAAR will perform the SKAT-MS(1,25), SKAT-MS(1,1), Burden-MS(1,25), Burden-MS(1,1), ACAT-V-MS(1,25), ACAT-V-MS(1,1) and ACAT-O-MS tests (default = NULL).
rv_num_cutoff	the cutoff of minimum number of variants of analyzing a given variant-set (default = 2).

Value

a list with the following members:

num_variant: the number of variants with combined minor allele frequency > 0 and less than rare_maf_cutoff in the given variant-set that are used for performing the variant-set test using MetaSTAAR.

cMAC: the combined cumulative minor allele count of variants with combined minor allele frequency > 0 and less than rare_maf_cutoff in the given variant-set.

results_MetaSTAAR_O_cond: the conditional MetaSTAAR-O p-value that aggregated conditional SKAT-MS(1,25), SKAT-MS(1,1), Burden-MS(1,25), Burden-MS(1,1), ACAT-V-MS(1,25), and ACAT-V-MS(1,1) together with conditional p-values of each test weighted by each annotation using Cauchy method.

results_ACAT_O_MS_cond: the conditional ACAT-O-MS p-value that aggregated conditional SKAT-MS(1,25), SKAT-MS(1,1), Burden-MS(1,25), Burden-MS(1,1), ACAT-V-MS(1,25), and ACAT-V-MS(1,1) using Cauchy method.

results_MetaSTAAR_S_1_25_cond: a vector of conditional MetaSTAAR-S(1,25) p-values, including conditional SKAT-MS(1,25) p-value weighted by MAF, the conditional SKAT-MS(1,25) p-values weighted by each annotation, and a conditional MetaSTAAR-S(1,25) p-value by aggregating these p-values using Cauchy method.

results_MetaSTAAR_S_1_1_cond: a vector of conditional MetaSTAAR-S(1,1) p-values, including conditional SKAT-MS(1,1) p-value weighted by MAF, the conditional SKAT-MS(1,1) p-values weighted by each annotation, and a conditional MetaSTAAR-S(1,1) p-value by aggregating these p-values using Cauchy method.

results_MetaSTAAR_B_1_25_cond: a vector of conditional MetaSTAAR-B(1,25) p-values, including conditional Burden-MS(1,25) p-value weighted by MAF, the conditional Burden-MS(1,25) p-values weighted by each annotation, and a conditional MetaSTAAR-B(1,25) p-value by aggregating these p-values using Cauchy method.

results_MetaSTAAR_B_1_1_cond: a vector of conditional MetaSTAAR-B(1,1) p-values, including conditional Burden-MS(1,1) p-value weighted by MAF, the conditional Burden-MS(1,1) p-values weighted by each annotation, and a conditional MetaSTAAR-B(1,1) p-value by aggregating these p-values using Cauchy method.

results_MetaSTAAR_A_1_25_cond: a vector of conditional MetaSTAAR-A(1,25) p-values, including conditional ACAT-V-MS(1,25) p-value weighted by MAF, the conditional ACAT-V-MS(1,25) p-values weighted by each annotation, and a conditional MetaSTAAR-A(1,25) p-value by aggregating these p-values using Cauchy method.

results_MetaSTAAR_A_1_1_cond: a vector of conditional MetaSTAAR-A(1,1) p-values, including conditional ACAT-V-MS(1,1) p-value weighted by MAF, the conditional ACAT-V-MS(1,1) p-values weighted by each annotation, and a conditional MetaSTAAR-A(1,1) p-value by aggregating these p-values using Cauchy method.

References

Li, X., et al. (2023). Powerful, scalable and resource-efficient meta-analysis of rare variant associations in large whole genome sequencing studies. Nature Genetics, 55(1), 154-164. (pub)

Li, X., Li, Z., et al. (2020). Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale. Nature Genetics 52(9), 969-983. (pub)

Liu, Y., et al. (2019). Acat: A fast and powerful p value combination method for rare-variant analysis in sequencing studies. The American Journal of Human Genetics 104(3), 410-421. (pub)

xihaoli/MetaSTAAR documentation built on Nov. 10, 2024, 5:26 a.m.