Under this model, extreme quantitative traits are simulated based on given percentile upper (\(p\)) and lower (\(q\)) bounds. There are two approaches to generate extreme QT values:
In SEQPower no specific statistical methods for analyzing extreme quantitative traits are implemented. To analyze data from this model, one can use methods for regular QT analysis with permutation testing to obtain p-value estimate, or implement via ''RTest'' interface some more sophisticated analysis methods.
spower ELNR -h
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usage: spower ELNR [-h] [-a MULTIPLIER] [-b MULTIPLIER] [-A MULTIPLIER] [-B MULTIPLIER] [-c MULTIPLIER] [-d MULTIPLIER] [--QT_thresholds C C] [--sample_size N] [--p1 P] [--def_rare P] [--def_neutral VALUE VALUE] [--def_protective VALUE VALUE] [-P P] [-Q P] [--def_valid_locus VALUE VALUE] [--rare_only] [--missing_as_wt] [--missing_low_maf P] [--missing_sites P] [--missing_sites_deleterious P] [--missing_sites_protective P] [--missing_sites_neutral P] [--missing_sites_synonymous P] [--missing_calls P] [--missing_calls_deleterious P] [--missing_calls_protective P] [--missing_calls_neutral P] [--missing_calls_synonymous P] [--error_calls P] [--error_calls_deleterious P] [--error_calls_protective P] [--error_calls_neutral P] [--error_calls_synonymous P] [--power P] [-r N] [--alpha ALPHA] [--moi {A,D,R,M}] [--resampling] [-l N] [-o file] [-t NAME] [-v {0,1,2,3}] [-s N] [-j N] [-m METHODS [METHODS ...]] [--discard_samples [EXPR [EXPR ...]]] [--discard_variants [EXPR [EXPR ...]]] DATA positional arguments: DATA name of input data or prefix of input data bundle (see the documentation for details) optional arguments: -h, --help show this help message and exit model parameters: -a MULTIPLIER, --meanshift_rare_detrimental MULTIPLIER mean shift in quantitative value w.r.t standard deviation due to detrimental rare variants i.e., by "MULTIPLIER * sigma" (default set to 0.0) -b MULTIPLIER, --meanshift_rare_protective MULTIPLIER mean shift in quantitative value w.r.t. standard deviation due to protective rare variants i.e., by "MULTIPLIER * sigma" (default set to 0.0) -A MULTIPLIER, --meanshiftmax_rare_detrimental MULTIPLIER maximum mean shift in quantitative value w.r.t standard deviation due to detrimental rare variants i.e., by "MULTIPLIER * sigma", applicable to variable effects model (default set to None) -B MULTIPLIER, --meanshiftmax_rare_protective MULTIPLIER maximum mean shift in quantitative value w.r.t standard deviation due to protective rare variants i.e., by "MULTIPLIER * sigma", applicable to variable effects model (default set to None) -c MULTIPLIER, --meanshift_common_detrimental MULTIPLIER mean shift in quantitative value w.r.t standard deviation due to detrimental common variants i.e., by "MULTIPLIER * sigma" (default set to 0.0) -d MULTIPLIER, --meanshift_common_protective MULTIPLIER mean shift in quantitative value w.r.t standard deviation due to protective common variants i.e., by "MULTIPLIER * sigma" (default set to 0.0) --QT_thresholds C C lower/uppwer percentile cutoffs for quantitative traits in extreme QT sampling, default to "0.5 0.5" --moi {A,D,R,M} mode of inheritance: "A", additive (default); "D", dominant; "R", recessive; "M", multiplicative (does not apply to quantitative traits model) --resampling directly draw sample genotypes from given haplotype pools (sample genotypes will be simulated on the fly if haplotype pools are not avaliable) sample population: --sample_size N total sample size --p1 P proportion of affected individuals (default set to 0.5), or individuals with high extreme QT values sampled from infinite population (default set to None, meaning to sample from finite population speficied by --sample_size option). variants functionality: --def_rare P definition of rare variants: variant having "MAF <= frequency" will be considered a "rare" variant; the opposite set is considered "common" (default set to 0.01) --def_neutral VALUE VALUE annotation value cut-offs that defines a variant to be "neutral" (e.g. synonymous, non-coding etc. that will not contribute to any phenotype); any variant with "function_score" X falling in this range will be considered neutral (default set to None) --def_protective VALUE VALUE annotation value cut-offs that defines a variant to be "protective" (i.e., decrease disease risk or decrease quantitative traits value); any variant with "function_score" X falling in this range will be considered protective (default set to None) -P P, --proportion_detrimental P proportion of deleterious variants associated with the trait of interest, i.e., the random set of the rest (1 - p) x 100% deleterious variants are non-causal: they do not contribute to the phenotype in simulations yet will present as noise in analysis (default set to None) -Q P, --proportion_protective P proportion of protective variants associated with the trait of interest, i.e., the random set of the rest (1 - p) x 100% protective variants are non-causal: they do not contribute to the phenotype in simulations yet will present as noise in analysis (default set to None) quality control: --def_valid_locus VALUE VALUE upper and lower bounds of variant counts that defines if a locus is "valid", i.e., locus having number of variants falling out of this range will be ignored from power calculation (default set to None) --rare_only remove from analysis common variant sites in the population, i.e., those in the haplotype pool having MAF > $def_rare --missing_as_wt label missing genotype calls as wildtype genotypes sequencing / genotyping artifact: --missing_low_maf P variant sites having population MAF < P are set to missing --missing_sites P proportion of missing variant sites --missing_sites_deleterious P proportion of missing deleterious sites --missing_sites_protective P proportion of missing protective sites --missing_sites_neutral P proportion of missing neutral sites --missing_sites_synonymous P proportion of missing synonymous sites --missing_calls P proportion of missing genotype calls --missing_calls_deleterious P proportion of missing genotype calls at deleterious sites --missing_calls_protective P proportion of missing genotype calls at protective sites --missing_calls_neutral P proportion of missing genotype calls at neutral sites --missing_calls_synonymous P proportion of missing genotype calls at synonymous sites --error_calls P proportion of error genotype calls --error_calls_deleterious P proportion of error genotype calls at deleterious sites --error_calls_protective P proportion of error genotype calls at protective sites --error_calls_neutral P proportion of error genotype calls at neutral sites --error_calls_synonymous P proportion of error genotype calls at synonymous sites power calculation: --power P power for which total sample size is calculated (this option is mutually exclusive with option '-- sample_size') -r N, --replicates N number of replicates for power evaluation (default set to 1) --alpha ALPHA significance level at which power will be evaluated (default set to 0.05) input/output specifications: -l N, --limit N if specified, will limit calculations to the first N groups in data (default set to None) -o file, --output file output filename runtime options: -t NAME, --title NAME unique identifier of a single command run (default to output filename prefix) -v {0,1,2,3}, --verbosity {0,1,2,3} verbosity level: 0 for absolutely quiet, 1 for less verbose, 2 for verbose, 3 for more debug information (default set to 2) -s N, --seed N seed for random number generator, 0 for random seed (default set to 0) -j N, --jobs N number of CPUs to use when multiple replicates are required via "-r" option (default set to 2) association tests: -m METHODS [METHODS ...], --methods METHODS [METHODS ...] Method of one or more association tests. Parameters for each method should be specified together as a quoted long argument (e.g. --methods "m --alternative 2" "m1 --permute 1000"), although the common method parameters can be specified separately, as long as they do not conflict with command arguments. (e.g. --methods m1 m2 -p 1000 is equivalent to --methods "m1 -p 1000" "m2 -p 1000".). You can use command 'spower show tests' for a list of association tests, and 'spower show test TST' for details about a test. samples and genotypes filtering: --discard_samples [EXPR [EXPR ...]] Discard samples that match specified conditions within each test group. Currently only expressions in the form of "%(NA)>p" is provided to remove samples that have more 100*p percent of missing values. --discard_variants [EXPR [EXPR ...]] Discard variant sites based on specified conditions within each test group. Currently only expressions in the form of '%(NA)>p' is provided to remove variant sites that have more than 100*p percent of missing genotypes. Note that this filter will be applied after "--discard_samples" is applied, if the latter also is specified.
Model specific options are similar to options in ''LNR'' model. General simulation and analysis options are otherwise documented. The infinite sample pool method is triggered by --p1
option. If --p1
is not specified, the finite sample pool method will be used.
This option takes two values, the lower and upper QT percentile cutoff which defines case control status. QT values under the lower cutoff are considered controls; QT values higher than the upper cutoff are considered cases.