GPC              package:GeneticsDesign              R Documentation

_G_e_n_e_t_i_c_s _p_o_w_e_r _c_a_l_c_u_l_a_t_o_r _f_o_r _l_i_n_e_a_r _t_r_e_n_d _a_s_s_o_c_i_a_t_i_o_n _s_t_u_d_i_e_s

_D_e_s_c_r_i_p_t_i_o_n:

     Genetics power calculator for linear trend association studies.

_U_s_a_g_e:

       GPC(pA, pD, RRAa, RRAA, r2, pB, 
                   nCase=500, ratio=1, alpha=0.05, quiet=FALSE)
       GPC.default(pA, pD, RRAa, RRAA, Dprime, pB, 
                   nCase=500, ratio=1, alpha=0.05, quiet=FALSE)

_A_r_g_u_m_e_n_t_s:

      pA: High risk allele frequency ('A').

      pD: Disease prevalence.

    RRAa: Genotype relative risk ('Aa') =
          'RR(Aa|aa)=Pr(D|Aa)/Pr(D|aa)'.

    RRAA: Genotype relative risk ('AA') =
          'RR(AA|aa)=Pr(D|AA)/Pr(D|aa)'.

      r2: LD measure. Assume that 'D > 0'.

  Dprime: LD measure.

      pB: Marker allele frequency ('B').

   nCase: Number of cases.

   ratio: Control:case ratio '= nControl/nCase'.

   alpha: User-defined type I error rate.

   quiet: Print some intermediate results if 'quiet=FALSE'.

_D_e_t_a_i_l_s:

     The power is for the test that disease is associated with a
     marker, given high risk allele frequency ('A'), disease
     prevalence, genotype relative risk ('Aa'), genotype relative risk
     ('AA'), LD measure ('D'' or 'r^2'), marker allele frequency ('B'),
     number of cases, control:case ratio, and probability of the Type I
     error. The linear trend test (Cochran 1954; Armitage 1955) is
     used.

_V_a_l_u_e:

   power: The estimated power for the association test.

     ncp: Non-centrality parameter.

mat.para: A matrix of case-control parameters, including number of
          cases, number of controls, high risk allele frequency,
          prevalence, genotypic relative risk ('Aa'), genotypic
          relative risk ('AA'), genotypic risk for 'aa' (baseline).

   mat.B: A matrix of marker locus 'B' parameters, including marker
          allele frequency, linkage disequilibrium ('D''), penetrance
          at marker genotype 'bb', penetrance at marker genotype 'Bb',
          penetrance at marker genotype 'BB', genotypic odds ratio
          'Bb', genotypic odds ratio 'BB'.

mat.aFreq: A 2 by 2 matrix of expected allele frequencies 'Pr(B|D),
          Pr(b|D), Pr(B|non D), Pr(b|non D)'.

mat.gFreq: A 3 by 2 matrix of expected genotype frequencies 'Pr(BB|D),
          Pr(Bb|D), Pr(bb|D), Pr(BB|non D), Pr(Bb|non D), Pr(bb|non
          D)'.

mat.stat: Power estimates for a sequence of Type I errors.

_A_u_t_h_o_r(_s):

     Weiliang Qiu stwxq@channing.harvard.edu, Ross Lazarus
     ross.lazarus@channing.harvard.edu

_R_e_f_e_r_e_n_c_e_s:

     Armitage, P. (1955)  Tests for linear trends in proportions and
     frequencies.  _Biometrics_, 11, 375-386.

     Cochran, W.G. (1954)  Some methods for strengthening the common
     chi-squared tests.  _Biometrics_, 10, 417-451.

     Gordon D, Finch SJ, Nothnagel M, Ott J (2002)  Power and sample
     size calculations for case-control genetic association tests when
     errors are present: application to single nucleotide
     polymorphisms.  _Hum. Hered._, 54:22-33.

     Gordon D, Haynes C, Blumenfeld J, Finch SJ (2005)  PAWE-3D:
     visualizing Power for Association With Error in case/control
     genetic studies of complex traits.  _Bioinformatics_,
     21:3935-3937.

     Purcell S, Cherny SS, Sham PC. (2003). Genetic Power Calculator:
     design of linkage and association genetic mapping  studies of
     complex traits.  _Bioinformatics_, 19(1):149-150.

     Sham P. (1998). _Statistics in Human Genetics._ Arnold
     Applications of Statistics.

_E_x_a_m_p_l_e_s:

       res1<-GPC(pA=0.05, pD=0.1, RRAa=1.414, RRAA=2, r2=0.9, pB=0.06, 
                        nCase=500, ratio=1, alpha=0.05, quiet=FALSE)

       res2<-GPC.default(pA=0.05, pD=0.1, RRAa=1.414, RRAA=2, Dprime=0.9, pB=0.06, 
                        nCase=500, ratio=1, alpha=0.05, quiet=FALSE)

