get.scores.pvalues: function to compute scores and p-values
In fat2Lpoly: Two-Locus Family-Based Association Test with Polytomous Outcome

Description Usage Arguments Value Author(s) See Also Examples

For each tested SNP and each parameter in the model, computes scores by summing family scores over all families and computes the corresponding p-values. P-values of global and joint tests are also computed.

1	get.scores.pvalues(test, joint.tests)

`test`	object returned by `fat2Lpoly.withinR`.
`joint.tests`	list of vectors of numbers between 1 and the total number of parameters in the `design` function. Each vector gives parameter indices to test the corresponding parameters jointly.

data frame of p-values for all the tested SNPs, for the global test (all parameters tested jointly), the individual tests and other joint tests specified by the argument joint.tests. The p-values are obtained from scores summed over all families. These scores of individual tests are also included in this data frame.

Alexandre Bureau and Jordie Croteau

fat2Lpoly, fat2Lpoly.withinR

data(fat2Lpoly.allSNPs)
			   
joint.tests=list(c(2,5),c(3,4))

get.scores.pvalues(fat2Lpoly.allSNPs, joint.tests)	
			   
#    snp.cond  snp.test global_p params.joint_2-5_p params.joint_3-4_p param_1_score 
# 1 snp4.loc1 snp2.loc2 5.80e-03           7.12e-01           0.000954         0.449 
# 2 snp4.loc1 snp4.loc2 2.14e-07           1.24e-05           0.000954         0.449 
# 3 snp4.loc1 snp5.loc2 1.14e-03           1.44e-01           0.000954         0.449 
# 4 snp4.loc1 snp6.loc2 5.59e-04           3.84e-02           0.000954         0.449 
# 5 snp4.loc1 snp8.loc2 1.15e-03           1.55e-01           0.000954         0.449 
# param_2_score param_3_score param_4_score param_5_score param_1_p param_2_p
#         0.333        -1.427         3.638         0.733     0.653     0.739
#         0.890        -1.427         3.638         4.612     0.653     0.373		
#         0.776        -1.427         3.638         1.785     0.653     0.438
#        -0.082        -1.427         3.638         2.553     0.653     0.934
#         0.869        -1.427         3.638         1.695     0.653     0.385		
#   param_3_p param_4_p param_5_p
# 1     0.154  0.000275  0.464000
# 2     0.154  0.000275  0.000004
# 3     0.154  0.000275  0.074200
# 4     0.154  0.000275  0.010700
# 5     0.154  0.000275  0.090100