Relationship-Informed Pedigree and Variant Scoring


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Documentation for package ‘KinformR’ version 0.1.2

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add.fam.scores Sum all the given scores and return a single vector with cumulative "score", "for" and "against" vals. For use in instances where one wishes to combine scores from multiple families.
assign.a For affecteds: Take genetic variant and determine the category of the combo.
assign.status Take a disease status and a genetic variant and determine which category the combo falls in. A.c = Affected individual with ALT variant A.i = Affected individual without ALT variant U.c = Unaffected individual without ALT variant U.i = Unaffected individual with ALT variant If theoretical.max = TRUE the true variant statuses are ignored and all affected/unaffected are assigned A.c and U.c respectively. These encoding can then be used show what a family's max score would be.
assign.u For unaffecteds: Take a genetic variant and determine the category of the combo.
build.relation.dict Build dictionary with the relationships falling in the different categories for the query row.
calc.rv.score Calculate a relatedness-weighted score for a given rare variant.
encode.rows Take the relationship matrix and the encoded statuses of info. For each row, generate the encoded data for scoring.
ibd Calculation of Identity by descent (IBD).
penetrance Likelihood function for calculation of Pedigree-based autosomal dominant penetrance value. Formula deployed via optimize so as to determine the optimal value.
read.indiv Read in variant and status info for individuals.
read.pedigree Read in the encoded pedigree data file.
read.relation.mat Read in relationship matrix Apply the individual names to the rows and columns.
read.var.table Read in a vcf-like subset of information obtained from use of seqbiopy's vcf_extract function on a vcf with the status encoded in the indivudal's names
score Score the pedigrees using the pihat values.
score.fam Given a relationship matrix and status dataframe, score a family by applying the calc.rv.score scoring system to every pairwise combination of individuals.
score.pedigree Take the encoded information about the pedigrees and calculate penetrance.
score.variant.status Take the dataframe with variants and status and determine which indivudals are scored correctly and which are scored incorrectly. Assign an A.c, A.i, U.c, U.i, unk
subset.mat Take the matrix and subset out only the encoded individuals that are present in the status dataframe.