qtlDesign (version 0.92)

mma: Selective phenotyping with similarity measure 2

Description

Selective phenotyping with similarity measure 2 to select the most dissimilar subset of individuals.

Usage

mma(genof, p, sequent = FALSE, exact = FALSE, dismat = FALSE)

Arguments

genof

Genotype matrix.

p

Sample size to select.

sequent

Perform sequential optimization if TRUE (see below).

exact

Count allele differences if FALSE; binary 0 = same number of alleles, 1 = different if TRUE.

dismat

Return dissimilarity matrix if TRUE.

Value

• A list containing cList, dismat if that option is TRUE and further optimized lists (op, op2, moment2) if sequent is TRUE. vector as the first item. The list of items includes:
• cList
  vector of selected subjects by function mma
• op
  list containing vector of selection and update flag from function op
• op2
  matrix of selection by function op2
• moment2
  vector of second moment calculations
• dismat
  dissimilarity matrix

Details

Sequentially minimize 1st moment and then 2nd moment, swapping one subject at a time. op finds all the samples with same 1st moment similarity with mma results. op2 finds all the samples with the same 1st moment similarity with every list from op result. A combination of op and op2 comes very close to exhaustive search in practice. moment2 find the best list with minimum 2nd moments from the output of op2. Note that some warnings occurs accompanying our return statement. The results are not affected though.

This function combines several functions in Jin's original code. mma(genof,p,sequent=TRUE is identical to the depricated mmasequent(genof,p. mma(genof,p,exact=TRUE is identical to the depricated mmaM1(genof,p (actually, mma uses dissimilarity while mmaM1 used similarity = 1 - dissimilarity).

References

Jin C, Lan H, Attie AD, Churchill GA, Bulutuglo D, Yandell BS (2004) Selective phenotyping for increased efficiency in genetic mapping studies. Genetics 168: 2285-2293.

See Also

K1, read.cross