MetaSTAAR: Meta-analysis of STAAR (MetaSTAAR) procedure using omnibus...
In xihaoli/MetaSTAAR: Meta-Analysis of STAAR (MetaSTAAR) Procedure for Dynamic Incorporation of Multiple Functional Annotations in Whole Genome Sequencing Studies
MetaSTAAR R Documentation
Meta-analysis of STAAR (MetaSTAAR) procedure using omnibus test
Description
The MetaSTAAR function takes in the object from the merged summary statistics
and covariance files of each individual study and functional annotation data
to analyze the association between a quantitative/dichotomous phenotype and
a variant-set by using the meta-analysis of STAAR (MetaSTAAR) procedure.
For each variant-set, the MetaSTAAR-O p-value is a p-value from an omnibus test
that aggregated 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 p-values of each test weighted by each annotation using Cauchy method.
Usage
MetaSTAAR(obj_MetaSTAAR_merge, annotation_phred = NULL, rv_num_cutoff = 2)
Arguments
obj_MetaSTAAR_merge
an object from merging the summary statistics
and covariance files from each participating study, which is the output from
MetaSTAAR_merge.
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: the MetaSTAAR-O p-value that aggregated 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 p-values of each test weighted by each annotation using Cauchy method.
results_ACAT_O_MS: the ACAT-O-MS p-value that aggregated 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: a vector of MetaSTAAR-S(1,25) p-values,
including SKAT-MS(1,25) p-value weighted by MAF, the SKAT-MS(1,25)
p-values weighted by each annotation, and a MetaSTAAR-S(1,25)
p-value by aggregating these p-values using Cauchy method.
results_MetaSTAAR_S_1_1: a vector of MetaSTAAR-S(1,1) p-values,
including SKAT-MS(1,1) p-value weighted by MAF, the SKAT-MS(1,1)
p-values weighted by each annotation, and a MetaSTAAR-S(1,1)
p-value by aggregating these p-values using Cauchy method.
results_MetaSTAAR_B_1_25: a vector of MetaSTAAR-B(1,25) p-values,
including Burden-MS(1,25) p-value weighted by MAF, the Burden-MS(1,25)
p-values weighted by each annotation, and a MetaSTAAR-B(1,25)
p-value by aggregating these p-values using Cauchy method.
results_MetaSTAAR_B_1_1: a vector of MetaSTAAR-B(1,1) p-values,
including Burden-MS(1,1) p-value weighted by MAF, the Burden-MS(1,1)
p-values weighted by each annotation, and a MetaSTAAR-B(1,1)
p-value by aggregating these p-values using Cauchy method.
results_MetaSTAAR_A_1_25: a vector of MetaSTAAR-A(1,25) p-values,
including ACAT-V-MS(1,25) p-value weighted by MAF, the ACAT-V-MS(1,25)
p-values weighted by each annotation, and a MetaSTAAR-A(1,25)
p-value by aggregating these p-values using Cauchy method.
results_MetaSTAAR_A_1_1: a vector of MetaSTAAR-A(1,1) p-values,
including ACAT-V-MS(1,1) p-value weighted by MAF, the ACAT-V-MS(1,1)
p-values weighted by each annotation, and a 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.
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| MetaSTAAR | R Documentation |
Meta-analysis of STAAR (MetaSTAAR) procedure using omnibus test
Description
The MetaSTAAR function takes in the object from the merged summary statistics
and covariance files of each individual study and functional annotation data
to analyze the association between a quantitative/dichotomous phenotype and
a variant-set by using the meta-analysis of STAAR (MetaSTAAR) procedure.
For each variant-set, the MetaSTAAR-O p-value is a p-value from an omnibus test
that aggregated 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 p-values of each test weighted by each annotation using Cauchy method.
Usage
MetaSTAAR(obj_MetaSTAAR_merge, annotation_phred = NULL, rv_num_cutoff = 2)
Arguments
obj_MetaSTAAR_merge |
an object from merging the summary statistics
and covariance files from each participating study, which is the output from
|
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: the MetaSTAAR-O p-value that aggregated 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 p-values of each test weighted by each annotation using Cauchy method.
results_ACAT_O_MS: the ACAT-O-MS p-value that aggregated 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: a vector of MetaSTAAR-S(1,25) p-values,
including SKAT-MS(1,25) p-value weighted by MAF, the SKAT-MS(1,25)
p-values weighted by each annotation, and a MetaSTAAR-S(1,25)
p-value by aggregating these p-values using Cauchy method.
results_MetaSTAAR_S_1_1: a vector of MetaSTAAR-S(1,1) p-values,
including SKAT-MS(1,1) p-value weighted by MAF, the SKAT-MS(1,1)
p-values weighted by each annotation, and a MetaSTAAR-S(1,1)
p-value by aggregating these p-values using Cauchy method.
results_MetaSTAAR_B_1_25: a vector of MetaSTAAR-B(1,25) p-values,
including Burden-MS(1,25) p-value weighted by MAF, the Burden-MS(1,25)
p-values weighted by each annotation, and a MetaSTAAR-B(1,25)
p-value by aggregating these p-values using Cauchy method.
results_MetaSTAAR_B_1_1: a vector of MetaSTAAR-B(1,1) p-values,
including Burden-MS(1,1) p-value weighted by MAF, the Burden-MS(1,1)
p-values weighted by each annotation, and a MetaSTAAR-B(1,1)
p-value by aggregating these p-values using Cauchy method.
results_MetaSTAAR_A_1_25: a vector of MetaSTAAR-A(1,25) p-values,
including ACAT-V-MS(1,25) p-value weighted by MAF, the ACAT-V-MS(1,25)
p-values weighted by each annotation, and a MetaSTAAR-A(1,25)
p-value by aggregating these p-values using Cauchy method.
results_MetaSTAAR_A_1_1: a vector of MetaSTAAR-A(1,1) p-values,
including ACAT-V-MS(1,1) p-value weighted by MAF, the ACAT-V-MS(1,1)
p-values weighted by each annotation, and a 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)
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