conditional_tdt: The DTT with a TDT-like test statistic
In stephenbates19/digitaltwins: Causal inference for SNPs

Description Usage Arguments Details Value

Runs the local Digital Twin Test using the TDT test statistc. This test determines if there is a causal SNP somewhere in a specified windown, after accounting for all genetic variant outside the window.

1 2	conditional_tdt(sample, haps_matrix, snp_info, group, site, gen_map, n_reps = 500, exact = FALSE)

`sample`	A dataframe in .sample format. `sample$father` gives the index of the father in the `haps_matrix`, and the `sample$mother` gives the index of the the mother in the `haps_matrix`.
`haps_matrix`	A n x p matrix of 0-1. Each row represents one haplotypes. To convert from indices to haplotype indices, an entry i in `sample$father` corresponds to the two rows 2i - 1 and 2i in `haps_matrix`.
`snp_info`	A dataframe with 5 columns: chromosome, snp_name, position, variant_1, and variant_2 (column naming is ignored).
`group`	A vector of entries specifying the group to test. Must be a vector of the form j:k for some j > 0 and k < p + 1.
`site`	The index of a column of `haps_matrix` to test. This is analagous to the variant tested by the TDT.
`gen_map`	Genetic map: a dataframe contining at least columns "pposition" and "gposition".
`n_reps`	Number of repetions of the randomization test.
`exact`	Whether or not to include the finite-sample correction.