# The `haplo.stats`

Package

## Overview of haplo.stats

Routines for the analysis of indirectly measured haplotypes. The
statistical methods assume that all subjects are unrelated and that
haplotypes are ambiguous (due to unknown linkage phase of the genetic
markers).

The main functions are described below.

## haplo.em

Estimation of haplotype frequencies, and posterior probabilities of
haplotype pairs for a subject, conditional on the observed marker
data.

## haplo.glm

GLM regression models for the regression of a trait on haplotypes,
possibly including covariates and interactions. S3 methods for anova and
summary have been implemented.

## haplo.score

Score statistics to test associations between haplotypes and a wide
variety of traits, including binary, ordinal, quantitative, and
Poisson.

## haplo.design

Uses as input the result from haplo.em(), and makes a design matrix
for haplotype dosage, such that modeling haplotypes is similar to how it
would be done within haplo.glm(), but without the iteratetively
re-weighted least squares steps.

## haplo.cc

Runs simple haplo.score and haplo.glm without covariates with
combined results for case-control (binomial family) response.