This implements the variable thresholds version of aggregation methods?. Similar to the VT? method, the VariableThresholdsBt and VariableThresholdsQt tests use a variable thresholds definition for the rare variants being considered such that multiple test statistics are calculated for an aggregation unit. The final statistic is taken as the one that gives the best result. Type I error is controlled due to the use of permutation testing.
Results from variable thresholds methods have one additional column, i.e., an MAF column reporting the statistic of VT at which it is derived.
vtools show test VariableThresholdsBt
Name: VariableThresholdsBt
Description: Variable thresholds method for disease traits, in the spirit of Price
et al 2010
usage: vtools associate --method VariableThresholdsBt [-h] [--name NAME]
[-q1 MAFUPPER]
[-q2 MAFLOWER]
[--alternative TAILED]
[-p N] [--permute_by XY]
[--adaptive C]
[--NA_adjust]
[--moi {additive,dominant,recessive}]
Variable thresholds in burden test for disease traits (in the spirit of Price
et al 2010). The burden test statistic of a group of variants will be
maximized over subsets of variants defined by applying different minor allele
frequency thresholds. Significance of the statistic obtained is evaluated via
permutation
optional arguments:
-h, --help show this help message and exit
--name NAME Name of the test that will be appended to names of
output fields, usually used to differentiate output of
different tests, or the same test with different
parameters.
-q1 MAFUPPER, --mafupper MAFUPPER
Minor allele frequency upper limit. All variants
having sample MAF<=m1 will be included in analysis.
Default set to 1.0
-q2 MAFLOWER, --maflower MAFLOWER
Minor allele frequency lower limit. All variants
having sample MAF>m2 will be included in analysis.
Default set to 0.0
--alternative TAILED Alternative hypothesis is one-sided ("1") or two-sided
("2"). Default set to 1
-p N, --permutations N
Number of permutations
--permute_by XY Permute phenotypes ("Y") or genotypes ("X"). Default
is "Y"
--adaptive C Adaptive permutation using Edwin Wilson 95 percent
confidence interval for binomial distribution. The
program will compute a p-value every 1000 permutations
and compare the lower bound of the 95 percent CI of
p-value against "C", and quit permutations with the
p-value if it is larger than "C". It is recommended to
specify a "C" that is slightly larger than the
significance level for the study. To disable the
adaptive procedure, set C=1. Default is C=0.1
--NA_adjust This option, if evoked, will replace missing genotype
values with a score relative to sample allele
frequencies. The association test will be adjusted to
incorporate the information. This is an effective
approach to control for type I error due to
differential degrees of missing genotypes among
samples.
--moi {additive,dominant,recessive}
Mode of inheritance. Will code genotypes as 0/1/2/NA
for additive mode, 0/1/NA for dominant or recessive
model. Default set to additive
vtools show test VariableThresholdsQt
Name: VariableThresholdsQt
Description: Variable thresholds method for quantitative traits, in the spirit of
Price et al 2010
usage: vtools associate --method VariableThresholdsQt [-h] [--name NAME]
[-q1 MAFUPPER]
[-q2 MAFLOWER]
[--alternative TAILED]
[-p N] [--permute_by XY]
[--adaptive C]
[--NA_adjust]
[--moi {additive,dominant,recessive}]
Variable thresholds in burden test for quantitative traits (in the spirit of
Price et al 2010). The burden test statistic of a group of variants will be
maximized over subsets of variants defined by applying different minor allele
frequency thresholds. Significance of the statistic obtained is evaluated via
permutation
optional arguments:
-h, --help show this help message and exit
--name NAME Name of the test that will be appended to names of
output fields, usually used to differentiate output of
different tests, or the same test with different
parameters.
-q1 MAFUPPER, --mafupper MAFUPPER
Minor allele frequency upper limit. All variants
having sample MAF<=m1 will be included in analysis.
Default set to 1.0
-q2 MAFLOWER, --maflower MAFLOWER
Minor allele frequency lower limit. All variants
having sample MAF>m2 will be included in analysis.
Default set to 0.0
--alternative TAILED Alternative hypothesis is one-sided ("1") or two-sided
("2"). Default set to 1
-p N, --permutations N
Number of permutations
--permute_by XY Permute phenotypes ("Y") or genotypes ("X"). Default
is "Y"
--adaptive C Adaptive permutation using Edwin Wilson 95 percent
confidence interval for binomial distribution. The
program will compute a p-value every 1000 permutations
and compare the lower bound of the 95 percent CI of
p-value against "C", and quit permutations with the
p-value if it is larger than "C". It is recommended to
specify a "C" that is slightly larger than the
significance level for the study. To disable the
adaptive procedure, set C=1. Default is C=0.1
--NA_adjust This option, if evoked, will replace missing genotype
values with a score relative to sample allele
frequencies. The association test will be adjusted to
incorporate the information. This is an effective
approach to control for type I error due to
differential degrees of missing genotypes among
samples.
--moi {additive,dominant,recessive}
Mode of inheritance. Will code genotypes as 0/1/2/NA
for additive mode, 0/1/NA for dominant or recessive
mode. Default set to additive
Example using snapshot
vt_ExomeAssociation
vtools associate rare status --covariates age gender bmi exposure -m "VariableThresholdsBt \
--name VariableThresholdsBt --alternative 2 -p 5000 --permute_by X --adaptive 0.05" --group\
_by name2 --to_db variablethresholdsBt -j8 > variablethresholdsBt.txt
vtools show fields | grep variablethresholdsBt.txt
head variablethresholdsBt.txt
vtools associate rare bmi --covariates age gender exposure -m "VariableThresholdsQt --name \
VariableThresholdsQt --alternative 2 -p 5000 --permute_by X --adaptive 0.05" --group_by nam\
e2 --to_db variablethresholdsQt -j8 > variablethresholdsQt.txt
INFO: 3180 samples are found
INFO: 2632 groups are found
INFO: Starting 8 processes to load genotypes
Loading genotypes: 100% [=========================================================================================================================================] 3,180 34.2/s in 00:01:33
Testing for association: 100% [================================================================================================================================] 2,632/147 2.8/s in 00:15:35
INFO: Association tests on 2632 groups have completed. 147 failed.
INFO: Using annotation DB variablethresholdsQt in project test.
INFO: Annotation database used to record results of association tests. Created on Thu, 31 Jan 2013 22:54:27
vtools show fields | grep variablethresholdsQt.txt
variablethresholdsQt.name2 name2
variablethresholdsQt.sample_size_VariableThresholdsQt sample size
variablethresholdsQt.num_variants_VariableThresholdsQt number of variants in each group (adjusted for specified MAF
upper/lower bounds)
variablethresholdsQt.total_mac_VariableThresholdsQt total minor allele counts in a group (adjusted for MOI)
variablethresholdsQt.beta_x_VariableThresholdsQt test statistic. In the context of regression this is estimate of
effect size for x
variablethresholdsQt.pvalue_VariableThresholdsQt p-value
variablethresholdsQt.std_error_VariableThresholdsQt Empirical estimate of the standard deviation of statistic under the
null
variablethresholdsQt.num_permutations_VariableThresholdsQt number of permutations at which p-value is evaluated
variablethresholdsQt.MAF_threshold_VariableThresholdsQt The minor allele frequency at which the test statistic is maximized
head variablethresholdsQt.txt
name2 sample_size_VariableThresholdsQt num_variants_VariableThresholdsQt total_mac_VariableThresholdsQt beta_x_VariableThresholdsQt pvalue_VariableThresholdsQt std_error_VariableThresholdsQt num_permutations_VariableThresholdsQt MAF_threshold_VariableThresholdsQt
ABCB10 3180 6 122 5.93777 0.247752 3.68504 1000 0.000157233
ABCD3 3180 3 42 -1.48612 0.301698 0.740477 1000 0.00267296
AADACL4 3180 5 138 -1.70538 0.151848 0.927952 1000 0.00157233
AAMP 3180 3 35 2.352 0.0666445 0.923285 3000 0.00220126
ABCB6 3180 7 151 1.98423 0.655345 3.83344 1000 0.000157233
ABI2 3180 1 25 0 0.993007 0 1000 0.00393082
ABHD1 3180 5 29 -1.81424 0.257742 1.19045 1000 0.000314465
ABCG8 3180 12 152 -3.48381 0.143856 1.26176 1000 0.000786164
ACAP3 3180 3 17 2.70541 0.281718 2.01218 1000 0.000314465
(:exampleend