Package: KinformR 0.1.2

Cameron M. Nugent

KinformR: Relationship-Informed Pedigree and Variant Scoring

Comparative evaluation of families and candidate variants in rare-variant association studies. The package can be used for two methodologically overlapping but distinct purposes. First, the prior to any genetic or genomic evaluation, evaluation of relative detection power of pedigrees, can direct recruitment efforts by showing which individuals not yet sampled would be the most meaningful additions to a study. Second, after sequencing and analysis, variants based on association with disease status and familial relationships of individuals, aids in variant prioritization. Methodology is described in Nugent (2025) <doi:10.1101/2025.10.06.25337426>.

Authors:Cameron M. Nugent [aut, cre]

KinformR_0.1.2.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
KinformR/json (API)

# Install 'KinformR' in R:
install.packages('KinformR', repos = c('https://sequencebio.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/sequencebio/kinformr/issues

On CRAN:

Conda:

bioinformaticsgeneticsgenomicspedigree-analysis

4.48 score 1 stars 5 scripts 208 downloads 15 exports 0 dependencies

Last updated from:f184639246. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK118
source / vignettesOK211
linux-releaseOK118
macos-releaseOK192
macos-oldrelOK164
windows-develOK109
windows-releaseOK79
windows-oldrelOK76
wasm-releaseOK89

Exports:add.fam.scoresassign.statusbuild.relation.dictcalc.rv.scoreencode.rowsibdpenetranceread.indivread.pedigreeread.relation.matread.var.tablescorescore.famscore.pedigreescore.variant.status

Dependencies:

KinformR - penetrance and idb informed scoring of families
Introduction | Estimating power of families | Load the library | The input data | Simplified summary of pedigrees | Encoding categories of relationships | Theoretical vs. current rankings | Note on a few special cases
Rendered fromKinformR-penetrance_and_ibd.Rmdusingknitr::rmarkdown

Last update: 2025-09-09
Started: 2025-06-12

KinformR - pedigree-informed rare variant association scoring
Introduction | Load the library | Input data | The relation matrix | The status file | Scoring a family | How scoring works | A Minimal example, scoring a variant from perspective of a single individual.
Rendered fromKinformR-variant_scoring.Rmdusingknitr::rmarkdown

Last update: 2025-09-09
Started: 2025-06-12

Readme and manuals

Help Manual

Help pageTopics
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.add.fam.scores
For affecteds: Take genetic variant and determine the category of the combo.assign.a
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.status
For unaffecteds: Take a genetic variant and determine the category of the combo.assign.u
Build dictionary with the relationships falling in the different categories for the query row.build.relation.dict
Calculate a relatedness-weighted score for a given rare variant.calc.rv.score
Take the relationship matrix and the encoded statuses of info. For each row, generate the encoded data for scoring.encode.rows
Calculation of Identity by descent (IBD).ibd
Likelihood function for calculation of Pedigree-based autosomal dominant penetrance value. Formula deployed via optimize so as to determine the optimal value.penetrance
Read in variant and status info for individuals.read.indiv
Read in the encoded pedigree data file.read.pedigree
Read in relationship matrix Apply the individual names to the rows and columns.read.relation.mat
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 namesread.var.table
Score the pedigrees using the pihat values.score
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.fam
Take the encoded information about the pedigrees and calculate penetrance.score.pedigree
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, unkscore.variant.status
Take the matrix and subset out only the encoded individuals that are present in the status dataframe.subset.mat