LD               package:GeneticsBase               R Documentation

_P_a_i_r_w_i_s_e _l_i_n_k_a_g_e _d_i_s_e_q_u_i_l_i_b_r_i_u_m _b_e_t_w_e_e_n _g_e_n_e_t_i_c _m_a_r_k_e_r_s.

_D_e_s_c_r_i_p_t_i_o_n:

     Compute pairwise linkage disequilibrium between genetic markers

_U_s_a_g_e:

     LD(object, pooling.threshold = 0.1, founderOnly = FALSE, quiet = TRUE )
     LDband(object, width=31,pooling.threshold=0.1, founderOnly=FALSE, quiet=TRUE)
     LDband.geneSet(object,width=31,pooling.threshold=0.1, founderOnly=FALSE, quiet=TRUE)
     LDdist.geneSet(object,posVec, maxDist, pooling.threshold=0.1, founderOnly=FALSE, quiet=TRUE)

     summary.LD(object, 
                which = c("D", "D'", "r", "R^2", "X^2", "P-value", "LOD", "n"), 
                rowsep, 
                digits = 3, ...)

_A_r_g_u_m_e_n_t_s:

  object: geneSet object 

   width: window width 

  posVec: marker position

 maxDist: size of the window based on distance

pooling.threshold: Threshold for LD calculation

   which: character string indicates which LD statistic should be print
          out 

  rowsep: separator for rows 

  digits: the desired number of digits after the decimal point  

founderOnly: Indicates if only founders are used to do the test.

   quiet: Indicates if intermediate results should be output

     ...: additional optional arguments

_D_e_t_a_i_l_s:

     Linkage disequilibrium (LD) is the non-random association of
     marker alleles and can arise from marker proximity or from
     selection bias.

     'LD' estimates the extent of LD for all pairs of genotypes
     contained in a 'object'.  'LDband' computes the extent of LD of
     markers within a window containing 'width' markers centered around
     each marker in 'object'.

     The current (temporary) code only computes LD for markers with
     exactly 2 variants.  For other markers, 'NA' is returned. 

     Three estimators of LD are computed:


   _D raw difference in frequency between the observed number of AB
        pairs and the expected number:

                        D = p(AB) - p(A)*p(B)


   _D' scaled D spanning the range [-1,1] 

                            D' = D / Dmax

        where, if D > 0:

                   Dmax = min( p(A)p(b), p(a)p(B) )

        or if D < 0:

                  Dmax = max( -p(A)p(B), -p(a)p(b) )


   _r correlation coefficient between the markers

              r = -D / sqrt( p(A) * p(a) * p(B) * p(b) )


     where

   - p(A) is defined as the observed probability of allele 'A' for
        marker 1, 

   - p(a) = 1-p(A) is defined as the observed probability of allele 'a'
        for marker 1, 

   - p(B) is defined as the observed probability of allele 'B' for
        marker 2, and 

   - p(b) = 1- p(B) is defined as the observed probability of allele
        'b' for marker 2, and 

   - p(AB) is defined as the probability of the marker allele pair
        'AB'. 

     For genotype data, AB/ab cannot be distinguished from aB/Ab.
     Consequently, we estimate p(AB) using maximum likelihood and use
     this value in the computations.

_V_a_l_u_e:

     'LD' returns an object of class 'LD', while 'LDband' and 'LDdist'
     return objects of classes 'LDband' and 'LDdist',  respectively. 
     All classes contain these slots:

    call: the matched call

       D: Linkage disequilibrium estimate

 Dprime : Scaled linkage disequilibrium estimate

    corr: Correlation coefficient

    nobs: Number of observations

   chisq: Chi-square statistic for linkage equilibrium (i.e.,
          D=D'=corr=0)

 p.value: Chi-square p-value for marker independence

     LOD: LOD scores

     tab: Description of 'tab'

statlist: Description of 'statlist'

   which: Description of 'which'

  object: Description of 'object'

_A_u_t_h_o_r(_s):

     Gregory R. Warnes warnes@bst.rochester.edu

_S_e_e _A_l_s_o:

     'geneSet-class', 'diseq'

_E_x_a_m_p_l_e_s:

     data(CAMP)

     ld <- LD(CAMP)
     print(ld)

     ldb <- LDband(CAMP)
     print(ldb)

     ldd <- LDdist(CAMP, posVec=1:8, maxDist=3)
     print(ldd)

