get.scores.pvalues: function to compute scores and p-values

Description

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.

Usage

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

Value

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.

Arguments

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.

Author

Alexandre Bureau and Jordie Croteau

Examples

Run this code

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