This is implementation for the KBAC statistic in Liu and Leal 2010[^Dajiang J. Liu and Suzanne M. Leal (2010) A Novel Adaptive Method for the Analysis of Next-Generation Sequencing Data to Detect Complex Trait Associations with Rare Variants Due to Gene Main Effects and Interactions. PLoS Genetics doi:10.1371/journal.pgen.1001156. http://dx.plos.org/10.1371/journal.pgen.1001156^]. It carries out case-control association testing for rare variants for whole exome association studies. Briefly, consider a gene of length n which harbors m rare variants. Genotype on the m variant sites & the disease status (case/control) are known for each individual. The program takes as input the m-site genotype and disease status (case/control) data files, and computes a p-value indicating the significance of association. Permutation has to be used to obtain valid p-values.
An R package is also available for use with standalone text dataset.
Note a couple of differences between this implementation and the original version:
--alternative 2 option implements the spirit of the RBT test[^Iuliana Ionita-Laza, Joseph D. Buxbaum, Nan M. Laird and Christoph Lange (2011) A New Testing Strategy to Identify Rare Variants with Either Risk or Protective Effect on Disease. PLoS Genetics doi:10.1371/journal.pgen.1001289. http://dx.plos.org/10.1371/journal.pgen.1001289^] by performing two KBAC tests under both protective and deleterious assumptions and use the larger of the two statistics thus calculated as the final KBAC statistic.vtools show test KBAC
Name: KBAC
Description: Kernel Based Adaptive Clustering method, Liu & Leal 2010
usage: vtools associate --method KBAC [-h] [--name NAME] [-q1 MAFUPPER]
[-q2 MAFLOWER] [--alternative TAILED]
[-p N] [--adaptive C]
[--moi {additive,dominant,recessive}]
Kernel Based Adaptive Clustering method, Liu & Leal 2010. Genotype pattern
frequencies, weighted by a hypergeometric density kernel function, is compared
for differences between cases and controls. p-value is calculated using
permutation for consistent estimate with different sample sizes (the
approximation method of the original publication is not implemented). Two-
sided KBAC test is implemented by calculating a second statistic with
case/ctrl label swapped, and the larger of the two statistic is used as two-
sided test statistic
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 0.01
-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
--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
--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
Example using snapshot
vt_ExomeAssociation
vtools associate rare status -m "KBAC --name kbac -p 5000" --group_by refGene.name2 --to_db\
kbac -j8 > kbac.txt
INFO: 3180 samples are found
INFO: 2632 groups are found
INFO: Starting 8 processes to load genotypes
Loading genotypes: 100% [=====================] 3,180 34.4/s in 00:01:32
Testing for association: 100% [=====================] 2,632/591 18.9/s in 00:02:19
INFO: Association tests on 2632 groups have completed. 591 failed.
INFO: Using annotation DB kbac in project test.
INFO: Annotation database used to record results of association tests. Created on Wed, 30 Jan 2013 05:26:43
vtools show fields | grep kbac
kbac.refGene_name2 refGene_name2
kbac.sample_size_kbac sample size
kbac.num_variants_kbac number of variants in each group (adjusted for specified MAF
kbac.total_mac_kbac total minor allele counts in a group (adjusted for MOI)
kbac.statistic_kbac test statistic.
kbac.pvalue_kbac p-value
kbac.std_error_kbac Empirical estimate of the standard deviation of statistic
kbac.num_permutations_kbac number of permutations at which p-value is evaluated
head kbac.txt
refGene_name2 sample_size_kbac num_variants_kbac total_mac_kbac statistic_kbac pvalue_kbac std_error_kbac num_permutations_kbac
ABCG5 3180 6 87 0.00610092 0.353646 0.00629806 1000
ABCB6 3180 7 151 0.00375831 0.633367 0.00807416 1000
ABCB10 3180 6 122 0.0157014 0.0973805 0.00733189 5000
ABCG8 3180 12 152 -0.00160383 0.876124 0.00861691 1000
ABCA4 3180 43 492 0.0293608 0.387612 0.0142427 1000
ABHD1 3180 5 29 -0.000709548 0.732268 0.00400521 1000
ABCA12 3180 28 312 0.015846 0.509491 0.011858 1000
ABL2 3180 4 41 0.000628395 0.553447 0.00456862 1000
ACADL 3180 5 65 0.00239811 0.501499 0.00545028 1000
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