trim_ped: Trim pedigree based on proband recall
In SimRVPedigree: Simulate Pedigrees Ascertained for a Rare Disease

Description Usage Arguments Details Value References See Also Examples

Primarily intended as an internal function, trim_ped chooses a proband and trims relatives based on the proband's probability of recalling his or her relatives.

1	trim_ped(ped_file, recall_probs = NULL)

`ped_file`	An object of class `ped`. A pedigree generated by `sim_ped` or `sim_RVped`, or an object created by the function `new.ped`. See details.
`recall_probs`	Numeric. The proband's recall probabilities for relatives, see details. If not supplied, the default value of four times kinship coefficient between the proband and the relative is used.

By default recall_probs is four times the kinship coefficient, as defined by Thompson (see references), between the proband and the probands relative, which results in a recall probability of 2^{-(n-1)} for a relative of degree n. Alternatively, the user may specify a list of recall probabilities of length l > 0, in which case the first l-1 items in recall_probs are the respective proband recall probabilities for relatives of degree 1, 2, ..., l-1, and the lth item in recall_probs is the proband's recall probability for all relatives of degree l or greater. For example if recall_probs = c(1) all relatives will be recalled by the proband with probability 1.

Occasionally, a trimmed family member must be retained to ensure that the pedigree can be plotted. When this occurs, family members who share a non-zero kinship coefficient with the proband are censored of all pertinent information, and will always have the following qualities:

availability status = 0
affected status = NA
birth year = NA
onset year = NA
death year = NA
RR = NA

Users who wish to use trim_ped for pedigrees not generated by sim_ped or sim_RVped must use new.ped to create an object of class ped. The ped object must contain the following variables for each pedigree member:

name	type	description
`FamID`	numeric	family identification number
`ID`	numeric	individual identification number
`dadID`	numeric	identification number of father
`momID`	numeric	identification number of mother
`sex`	numeric	gender identification; if male `sex = 0`, if female `sex = 1`
`affected`	logical	disease-affection status:
`proband`	logical	a proband identifier: `proband = TRUE` if the individual is the proband, and `FALSE` otherwise.
		`affected = TRUE` if affected by disease , and `FALSE` otherwise,
`birthYr`	numeric	the individual's birth year.
`onsetYr`	numeric	the individual's disease onset year, when applicable.
`deathYr`	numeric	the individual's death year, when applicable.
`RR`	numeric	the individual's relative risk of disease.
`available`	logical	availibility status;
		`available = TRUE` if available, and `FALSE` otherwise.

ped_trim The trimmed pedigree.

Nieuwoudt, Christina and Jones, Samantha J and Brooks-Wilson, Angela and Graham, Jinko (2018). Simulating Pedigrees Ascertained for Multiple Disease-Affected Relatives. Source Code for Biology and Medicine, 13:2.

Thompson, E. (2000). Statistical Inference from Genetic Data on Pedigrees. NSF-CBMS Regional Conference Series in Probability and Statistics, 6, I-169.

sim_RVped, sim_ped, new.ped

#Read in example pedigree to trim
data(EgPeds)
egPeds <- new.ped(EgPeds)

#plot example_ped using kinship2
plot(subset(egPeds, FamID == 1), location = "topright", cex = 0.85)
mtext("Original Pedigree", side = 3, line = 2)


## Trim pedigree examples
# Illustrate the effect of various settings for recall_probs
Recall_Probabilities <- list(c(1),
                             c(1, 0.5),
                             c(1, 0.25, 0.1))


for (k in 1:length(Recall_Probabilities)) {
   set.seed(2)
   #trim pedigree
   TrimPed <- trim_ped(ped_file = subset(egPeds, FamID == 1),
                       recall_probs = Recall_Probabilities[[k]])

   plot(TrimPed, location = "topright", cex = 0.85)
   mtext(paste0("recall_probs = (", sep = "",
                paste(Recall_Probabilities[[k]], collapse = ", "), ')' ),
                side = 3, line = 2 )
}