From 6128c0a6410c7767737810b0b69aa856a21a624a Mon Sep 17 00:00:00 2001 From: CNuge Date: Fri, 6 Jun 2025 13:42:19 -0300 Subject: [PATCH] rename throughout --- DESCRIPTION | 4 +-- ...io.variant.scoring.Rproj => KinformR.Rproj | 0 LICENSE | 2 +- R/io.R | 6 ++-- R/pedigree.r | 4 +-- R/relatedness.r | 4 +-- README.md | 32 +++++++++---------- man/read.indiv.Rd | 2 +- man/read.pedigree.Rd | 2 +- man/read.relation.mat.Rd | 2 +- man/read.var.table.Rd | 2 +- man/score.fam.Rd | 4 +-- man/score.pedigree.Rd | 2 +- tests/testthat.R | 4 +-- tests/testthat/test_encoding.R | 2 +- tests/testthat/test_io.r | 8 ++--- tests/testthat/test_multi_fam_full_workflow.r | 12 +++---- tests/testthat/test_pedigree_eval.R | 6 ++-- .../testthat/test_single_fam_full_workflow.r | 6 ++-- ...bd.Rmd => KinformR-penetrance_and_ibd.Rmd} | 8 ++--- ...oring.Rmd => KinformR-variant_scoring.Rmd} | 12 +++---- 21 files changed, 62 insertions(+), 62 deletions(-) rename seqbio.variant.scoring.Rproj => KinformR.Rproj (100%) rename vignettes/{seqbio.variant.scoring-penetrance_and_ibd.Rmd => KinformR-penetrance_and_ibd.Rmd} (96%) rename vignettes/{seqbio.variant.scoring-variant_scoring.Rmd => KinformR-variant_scoring.Rmd} (92%) diff --git a/DESCRIPTION b/DESCRIPTION index 64fcd65..9e59962 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,11 +1,11 @@ -Package: seqbio.variant.scoring +Package: KinformR Title: Relationship-informed pedigree and variant scoring Version: 0.1.0 Authors@R: person("Cameron", "Nugent", , "cam.nugent@sequencebio.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-1135-2605")) Description: - The seqbio.variant.scoring R package is meant to aid in comparative evaluation of families + The KinformR R package is meant to aid in 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 diff --git a/seqbio.variant.scoring.Rproj b/KinformR.Rproj similarity index 100% rename from seqbio.variant.scoring.Rproj rename to KinformR.Rproj diff --git a/LICENSE b/LICENSE index 9cd26d1..d30f53e 100644 --- a/LICENSE +++ b/LICENSE @@ -1,6 +1,6 @@ # MIT License -Copyright (c) 2025 seqbio.variant.scoring Sequence Bioinformatics Inc. +Copyright (c) 2025 KinformR Sequence Bioinformatics Inc. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal diff --git a/R/io.R b/R/io.R index 6b64245..cc7da22 100644 --- a/R/io.R +++ b/R/io.R @@ -7,7 +7,7 @@ #' MS-5678-1001 A 0/1 #' @return A data frame. #' @examples -#' tsv.name1 <-system.file('extdata/1234_ex2.tsv', package = 'seqbio.variant.scoring') +#' tsv.name1 <-system.file('extdata/1234_ex2.tsv', package = 'KinformR') #' id.df1 <- read.indiv(tsv.name1) #' @export read.indiv <- function(fname){ @@ -24,7 +24,7 @@ read.indiv <- function(fname){ #' @param fname The file with the relationship matrix information. #' @return A matrix with the relationships and individual ids as rownames and colnames. #' @examples -#' mat.name1 <-system.file('extdata/1234_ex2.mat', package = 'seqbio.variant.scoring') +#' mat.name1 <-system.file('extdata/1234_ex2.mat', package = 'KinformR') #' mat1 <- read.relation.mat(mat.name1) #' @export read.relation.mat <- function(fname){ @@ -57,7 +57,7 @@ read.relation.mat <- function(fname){ #' MS-5678-1001 A 0/1 #' @examples #' ex.infile <-system.file('extdata/example_vcf_extract_5678.tsv', -#' package = 'seqbio.variant.scoring') +#' package = 'KinformR') #' read.var.table(ex.infile) #' @export read.var.table <- function(fname){ diff --git a/R/pedigree.r b/R/pedigree.r index c81fc41..cf80331 100644 --- a/R/pedigree.r +++ b/R/pedigree.r @@ -95,7 +95,7 @@ score <- function(pihat) { #' #' @examples #' example.pedigree.file <- system.file('extdata/example_pedigree_encoding.tsv', -#' package = 'seqbio.variant.scoring') +#' package = 'KinformR') #' example.pedigree.df <- read.pedigree(example.pedigree.file) read.pedigree <- function(filename){ h <- read.table(filename, header=TRUE, sep="\t", @@ -132,7 +132,7 @@ read.pedigree <- function(filename){ #' #' @examples #' example.pedigree.file <-system.file('extdata/example_pedigree_encoding.tsv', -#' package = 'seqbio.variant.scoring') +#' package = 'KinformR') #' example.pedigree.df <- read.pedigree(example.pedigree.file) #' penetrance.df <- score.pedigree(example.pedigree.df) score.pedigree <- function(h){ diff --git a/R/relatedness.r b/R/relatedness.r index edc065b..b12974e 100644 --- a/R/relatedness.r +++ b/R/relatedness.r @@ -159,8 +159,8 @@ subset.mat <- function(mat.df, status.df){ #' of points for or against. This simplifies scoring and allows for fast filtering of poor quality variants. Default is 4. #' @return A labelled vector with names: score, score.for, score.against #' @examples -#' mat.name1<-system.file('extdata/1234_ex2.mat', package = 'seqbio.variant.scoring') -#' tsv.name1<-system.file('extdata/1234_ex2.tsv', package = 'seqbio.variant.scoring') +#' mat.name1<-system.file('extdata/1234_ex2.mat', package = 'KinformR') +#' tsv.name1<-system.file('extdata/1234_ex2.tsv', package = 'KinformR') #' mat.df <- read.relation.mat(mat.name1) #' ind.df <- read.indiv(tsv.name1) #' ind.df.status <- score.variant.status(ind.df) diff --git a/README.md b/README.md index 40544e9..c2310e1 100644 --- a/README.md +++ b/README.md @@ -1,43 +1,43 @@ -# seqbio.variant.scoring -## An R package for relationship-informed pedigree and variant scoring +# KinformR +## The Kinship Informer: An R package for relationship-informed pedigree and variant scoring ## Introduction -Family-based genetic studies are effective for identifying rare variants underlying heritable diseases, yet are often challenged by issues such as incomplete penetrance and the difficulty of prioritizing numerous candidate variants. The proportion of the genome with identity-by-descent (IBD) and estimates of penetrance are metrics that can show the value of different pedigrees in family-based studies. Additionally, IBD and the genotypes of individuals are combined by seqbio.variant.scoringto to score the value of candidate variants. +Family-based genetic studies are effective for identifying rare variants underlying heritable diseases, yet are often challenged by issues such as incomplete penetrance and the difficulty of prioritizing numerous candidate variants. The proportion of the genome with identity-by-descent (IBD) and estimates of penetrance are metrics that can show the value of different pedigrees in family-based studies. Additionally, IBD and the genotypes of individuals are combined by KinformRto to score the value of candidate variants. -The `seqbio.variant.scoring` R package is meant to aid in comparative evaluation of families and candidate variants in rare-variant association studies. The package can be used for two methodologically overlapping but distinct purposes: 1) prior to any genetic/genomic evaluation, evaluation of relative detection power of pedigrees, can direct recruitment efforts by showing which unsampled individuals would be the most meaningful additions to a study, and 2) after sequencing and analysis, variants based on association with disease status and familial relationships of individuals, aids in variant prioritization +The `KinformR` R package is meant to aid in comparative evaluation of families and candidate variants in rare-variant association studies. The package can be used for two methodologically overlapping but distinct purposes: 1) prior to any genetic/genomic evaluation, evaluation of relative detection power of pedigrees, can direct recruitment efforts by showing which unsampled individuals would be the most meaningful additions to a study, and 2) after sequencing and analysis, variants based on association with disease status and familial relationships of individuals, aids in variant prioritization ## Installation -The development version of `seqbio.variant.scoring` can be installed directly from GitHub. You'll need to have the R package `devtools` installed and loaded. Also note if the build_vignettes option is set to true, you will need to have the R package `knitr` installed. +The development version of `KinformR` can be installed directly from GitHub. You'll need to have the R package `devtools` installed and loaded. Also note if the build_vignettes option is set to true, you will need to have the R package `knitr` installed. ``` #install.packages("devtools") #install.packages("knitr") #required if build_vignettes = TRUE #library(devtools) -devtools::install_github("SequenceBio/seqbio.variant.scoring", build_vignettes = TRUE) -library(seqbio.variant.scoring) +devtools::install_github("SequenceBio/KinformR", build_vignettes = TRUE) +library(KinformR) ``` ## How it works The package's vignette contains detailed explanations of the functions and parameters. -For a walk through of the `seqbio.variant.scoring` functions for scoring the value of *families* based on penetrance and IBD, see the corresponging vignette file: -`vignettes/seqbio.variant.scoring-penetrance_and_ibd.Rmd` +For a walk through of the `KinformR` functions for scoring the value of *families* based on penetrance and IBD, see the corresponging vignette file: +`vignettes/KinformR-penetrance_and_ibd.Rmd` or within R, run: ``` -vignette('seqbio.variant.scoring-penetrance_and_ibd') +vignette('KinformR-penetrance_and_ibd') ``` -For a walk through of the `seqbio.variant.scoring` functions for scoring the value of *variants* within families, see the corresponging vignette file: -`vignettes/seqbio.variant.scoring-variant_scoring.Rmd` +For a walk through of the `KinformR` functions for scoring the value of *variants* within families, see the corresponging vignette file: +`vignettes/KinformR-variant_scoring.Rmd` or within R, run: ``` -vignette('seqbio.variant.scoring-variant_scoring') +vignette('KinformR-variant_scoring') ``` ## Scoring families @@ -46,7 +46,7 @@ vignette('seqbio.variant.scoring-variant_scoring') See the included example data, which encodes 14 families. See the accompanying vignette for more information on encoding pedigrees: ``` - example.pedigree.file <-system.file('extdata/example_pedigree_encoding.tsv', package = 'seqbio.variant.scoring') + example.pedigree.file <-system.file('extdata/example_pedigree_encoding.tsv', package = 'KinformR') ``` The data can be loaded with the following function: ``` @@ -67,7 +67,7 @@ When looking at shared rare variants across families, not all sets of affected a This input is a matrix containing all the pairwise relationships of individuals in a family. The row and column names are the individual IDs, and the intersecting value denotes the degree of relationship between the individuals (self = 0, 1st degree relations. = 1, etc. Unrelated individuals are given a value of -1). As of version `0.1.0` the relation matrix is a manually created file, where relationship values are assigned via manual inspection of the family pedigree. ``` -mat.name<-system.file('extdata/1234_ex2.mat', package = 'seqbio.variant.scoring') +mat.name<-system.file('extdata/1234_ex2.mat', package = 'KinformR') rel.mat <- read.relation.mat(mat.name) ``` @@ -77,7 +77,7 @@ rel.mat <- read.relation.mat(mat.name) This file includes the same individual IDs used in the relationship matrix as well as the disease and variant status for all individuals. ``` -tsv.name<-system.file('extdata/1234_ex2.tsv', package = 'seqbio.variant.scoring') +tsv.name<-system.file('extdata/1234_ex2.tsv', package = 'KinformR') ind.df <- read.indiv(tsv.name) ind.df.status <- score.variant.status(ex1234.df) diff --git a/man/read.indiv.Rd b/man/read.indiv.Rd index ec59145..d51ac5f 100644 --- a/man/read.indiv.Rd +++ b/man/read.indiv.Rd @@ -18,6 +18,6 @@ A data frame. Read in variant and status info for individuals. } \examples{ -tsv.name1 <-system.file('extdata/1234_ex2.tsv', package = 'seqbio.variant.scoring') +tsv.name1 <-system.file('extdata/1234_ex2.tsv', package = 'KinformR') id.df1 <- read.indiv(tsv.name1) } diff --git a/man/read.pedigree.Rd b/man/read.pedigree.Rd index 79d4210..b9e4ecf 100644 --- a/man/read.pedigree.Rd +++ b/man/read.pedigree.Rd @@ -17,6 +17,6 @@ Read in the encoded pedigree data file. } \examples{ example.pedigree.file <- system.file('extdata/example_pedigree_encoding.tsv', -package = 'seqbio.variant.scoring') +package = 'KinformR') example.pedigree.df <- read.pedigree(example.pedigree.file) } diff --git a/man/read.relation.mat.Rd b/man/read.relation.mat.Rd index cdf64e7..65592bb 100644 --- a/man/read.relation.mat.Rd +++ b/man/read.relation.mat.Rd @@ -18,6 +18,6 @@ Row/column intersections give the degree of relationship for the two individuals. 0 = self, -1 = unrelated. } \examples{ -mat.name1 <-system.file('extdata/1234_ex2.mat', package = 'seqbio.variant.scoring') +mat.name1 <-system.file('extdata/1234_ex2.mat', package = 'KinformR') mat1 <- read.relation.mat(mat.name1) } diff --git a/man/read.var.table.Rd b/man/read.var.table.Rd index ee7f129..2ad5848 100644 --- a/man/read.var.table.Rd +++ b/man/read.var.table.Rd @@ -26,6 +26,6 @@ be encoded in a specific fashion for you current purposes. } \examples{ ex.infile <-system.file('extdata/example_vcf_extract_5678.tsv', - package = 'seqbio.variant.scoring') + package = 'KinformR') read.var.table(ex.infile) } diff --git a/man/score.fam.Rd b/man/score.fam.Rd index 50dd576..3e7d09a 100644 --- a/man/score.fam.Rd +++ b/man/score.fam.Rd @@ -57,8 +57,8 @@ NOTE: if affected.only = True, the averages and sums are calculated using only t } } \examples{ -mat.name1<-system.file('extdata/1234_ex2.mat', package = 'seqbio.variant.scoring') -tsv.name1<-system.file('extdata/1234_ex2.tsv', package = 'seqbio.variant.scoring') +mat.name1<-system.file('extdata/1234_ex2.mat', package = 'KinformR') +tsv.name1<-system.file('extdata/1234_ex2.tsv', package = 'KinformR') mat.df <- read.relation.mat(mat.name1) ind.df <- read.indiv(tsv.name1) ind.df.status <- score.variant.status(ind.df) diff --git a/man/score.pedigree.Rd b/man/score.pedigree.Rd index 0a381ee..ff03942 100644 --- a/man/score.pedigree.Rd +++ b/man/score.pedigree.Rd @@ -37,7 +37,7 @@ Will slightly bias the result toward higher penetrance. } \examples{ example.pedigree.file <-system.file('extdata/example_pedigree_encoding.tsv', -package = 'seqbio.variant.scoring') +package = 'KinformR') example.pedigree.df <- read.pedigree(example.pedigree.file) penetrance.df <- score.pedigree(example.pedigree.df) } diff --git a/tests/testthat.R b/tests/testthat.R index e2341c4..f824997 100644 --- a/tests/testthat.R +++ b/tests/testthat.R @@ -1,5 +1,5 @@ library(testthat) -library(seqbio.variant.scoring) +library(KinformR) -test_check("seqbio.variant.scoring") +test_check("KinformR") diff --git a/tests/testthat/test_encoding.R b/tests/testthat/test_encoding.R index c38fa5d..3513a9d 100644 --- a/tests/testthat/test_encoding.R +++ b/tests/testthat/test_encoding.R @@ -28,7 +28,7 @@ test_that("Families are correctly encoded.", { expect_error(assign.status("U", "0|."), "Incompatible variant value! Supported encodings are: '0' '1' '0/0' '0/1' '0|0' '0|1'") #tsv.name1<-"Data/1234_ex2.tsv" - tsv.name1<-system.file('extdata/1234_ex2.tsv', package = 'seqbio.variant.scoring') + tsv.name1<-system.file('extdata/1234_ex2.tsv', package = 'KinformR') indiv.df <- read.indiv(tsv.name1) print("score values for a real family") diff --git a/tests/testthat/test_io.r b/tests/testthat/test_io.r index f1b1711..561dc8c 100644 --- a/tests/testthat/test_io.r +++ b/tests/testthat/test_io.r @@ -5,10 +5,10 @@ test_that("Data are read from files correctly", { #tsv.name1<-"extdata/1234_ex2.tsv" # TODO - switch all to this style - tsv.name1 <-system.file('extdata/1234_ex2.tsv', package = 'seqbio.variant.scoring') + tsv.name1 <-system.file('extdata/1234_ex2.tsv', package = 'KinformR') ex1234.df <- read.indiv(tsv.name1) #mat.name1<-"extdata/1234_ex2.mat" - mat.name1 <-system.file('extdata/1234_ex2.mat', package = 'seqbio.variant.scoring') + mat.name1 <-system.file('extdata/1234_ex2.mat', package = 'KinformR') ex1234.mat <- read.relation.mat(mat.name1) # TODO - could make an s3 class with the two data structures, have single func to # wrap this and read in both files. @@ -24,7 +24,7 @@ test_that("Data are read from files correctly", { "status" = c("A", "U", "U", "U", "A"), "variant" = c("0/1", "0/0", "0/0", "0/0", "0/1")) infile.test2 <-system.file('extdata/example_vcf_extract_5678.tsv', - package = 'seqbio.variant.scoring') + package = 'KinformR') test2.df <- read.var.table(infile.test2) expect_equal(test2.df, expected.test2) @@ -37,7 +37,7 @@ test_that("Data are read from files correctly", { "status" = c("U","U","A","A","U", "U","A","U","U"), "variant" = c("0|0","0|0","0|0","0|1","0|0","0|0","0|1","0|0","0|1")) infile.test3 <-system.file('extdata/example_vcf_extract_9876.tsv', - package = 'seqbio.variant.scoring') + package = 'KinformR') test3.df <- read.var.table(infile.test3) expect_equal(test3.df, expected.test3) diff --git a/tests/testthat/test_multi_fam_full_workflow.r b/tests/testthat/test_multi_fam_full_workflow.r index 612a416..b65a81b 100644 --- a/tests/testthat/test_multi_fam_full_workflow.r +++ b/tests/testthat/test_multi_fam_full_workflow.r @@ -3,14 +3,14 @@ test_that("Scoring of variant in family multiple families proceeds as expected", ################################## # test 1 - mat.name1<-system.file('extdata/5678_ex1.mat', package = 'seqbio.variant.scoring') - tsv.name1<-system.file('extdata/5678_ex1.tsv', package = 'seqbio.variant.scoring') + mat.name1<-system.file('extdata/5678_ex1.mat', package = 'KinformR') + tsv.name1<-system.file('extdata/5678_ex1.tsv', package = 'KinformR') - mat.name2<-system.file('extdata/9876_ex1.mat', package = 'seqbio.variant.scoring') - tsv.name2<-system.file('extdata/9876_ex1.tsv', package = 'seqbio.variant.scoring') + mat.name2<-system.file('extdata/9876_ex1.mat', package = 'KinformR') + tsv.name2<-system.file('extdata/9876_ex1.tsv', package = 'KinformR') - mat.name3<-system.file('extdata/5432_ex1.mat', package = 'seqbio.variant.scoring') - tsv.name3<-system.file('extdata/5432_ex1.tsv', package = 'seqbio.variant.scoring') + mat.name3<-system.file('extdata/5432_ex1.mat', package = 'KinformR') + tsv.name3<-system.file('extdata/5432_ex1.tsv', package = 'KinformR') mat.fnames <- c(mat.name1, mat.name2, mat.name3) tsv.names <- c(tsv.name1, tsv.name2, tsv.name3) diff --git a/tests/testthat/test_pedigree_eval.R b/tests/testthat/test_pedigree_eval.R index 3dddf04..d3f010b 100644 --- a/tests/testthat/test_pedigree_eval.R +++ b/tests/testthat/test_pedigree_eval.R @@ -2,20 +2,20 @@ test_that("Data are read from files correctly", { ################################## # test 1 - example.pedigree.file <-system.file('extdata/example_pedigree_encoding.tsv', package = 'seqbio.variant.scoring') + example.pedigree.file <-system.file('extdata/example_pedigree_encoding.tsv', package = 'KinformR') example.pedigree.df <- read.pedigree(example.pedigree.file) penetrance.df <- score.pedigree(example.pedigree.df) ################################## # test 2 - example.pedigree.file2 <-system.file('extdata/example_pedigree_encoding2.tsv', package = 'seqbio.variant.scoring') + example.pedigree.file2 <-system.file('extdata/example_pedigree_encoding2.tsv', package = 'KinformR') #example.pedigree.file2 <- "inst/extdata/example_pedigree_encoding2.tsv" example.pedigree.df2 <- read.pedigree(example.pedigree.file2) penetrance.df2 <- score.pedigree(example.pedigree.df2) ################################## # test 3 - example.pedigree.file3 <-system.file('extdata/example_pedigree_encoding3.tsv', package = 'seqbio.variant.scoring') + example.pedigree.file3 <-system.file('extdata/example_pedigree_encoding3.tsv', package = 'KinformR') #example.pedigree.file3 <- "inst/extdata/example_pedigree_encoding3.tsv" example.pedigree.df3 <- read.pedigree(example.pedigree.file3) penetrance.df3 <- score.pedigree(example.pedigree.df3) diff --git a/tests/testthat/test_single_fam_full_workflow.r b/tests/testthat/test_single_fam_full_workflow.r index 478edf1..b9627bd 100644 --- a/tests/testthat/test_single_fam_full_workflow.r +++ b/tests/testthat/test_single_fam_full_workflow.r @@ -1,12 +1,12 @@ -#library(seqbio.variant.scoring) +#library(KinformR) test_that("Scoring of variant in family single family proceeds as expected", { ################################## # test 1 - mat.name1<-system.file('extdata/1234_ex2.mat', package = 'seqbio.variant.scoring') + mat.name1<-system.file('extdata/1234_ex2.mat', package = 'KinformR') ex1234.mat <- read.relation.mat(mat.name1) - tsv.name1<-system.file('extdata/1234_ex2.tsv', package = 'seqbio.variant.scoring') + tsv.name1<-system.file('extdata/1234_ex2.tsv', package = 'KinformR') ex1234.df <- read.indiv(tsv.name1) ex1234.df.status <- score.variant.status(ex1234.df) diff --git a/vignettes/seqbio.variant.scoring-penetrance_and_ibd.Rmd b/vignettes/KinformR-penetrance_and_ibd.Rmd similarity index 96% rename from vignettes/seqbio.variant.scoring-penetrance_and_ibd.Rmd rename to vignettes/KinformR-penetrance_and_ibd.Rmd index dcca8f7..6c950dc 100644 --- a/vignettes/seqbio.variant.scoring-penetrance_and_ibd.Rmd +++ b/vignettes/KinformR-penetrance_and_ibd.Rmd @@ -1,16 +1,16 @@ --- -title: "seqbio.variant.scoring - penetrance and idb informed scoring of families" +title: "KinformR - penetrance and idb informed scoring of families" author: "Cameron M. Nugent" data: "`r Sys.Date()`" output: pdf_document #rmarkdown::html_vignette # vignette: > - %\VignetteIndexEntry{seqbio.variant.scoring-penetrance_and_ibd} + %\VignetteIndexEntry{KinformR-penetrance_and_ibd} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- ```{r loadlib, echo = TRUE, results = 'hide', message=FALSE, warning=FALSE} -library(seqbio.variant.scoring) +library(KinformR) ``` @@ -28,7 +28,7 @@ The `cal.penetrance` function generates both a theoretical ranking of the power The family power calculations depend on a single tab-delimited input file, where each row represents a family. The input file is read inusing the `read.pedigree` function. ```{r} -example.pedigree.file <-system.file('extdata/example_pedigree_encoding.tsv', package = 'seqbio.variant.scoring') +example.pedigree.file <-system.file('extdata/example_pedigree_encoding.tsv', package = 'KinformR') example.pedigree.df <- read.pedigree(example.pedigree.file) diff --git a/vignettes/seqbio.variant.scoring-variant_scoring.Rmd b/vignettes/KinformR-variant_scoring.Rmd similarity index 92% rename from vignettes/seqbio.variant.scoring-variant_scoring.Rmd rename to vignettes/KinformR-variant_scoring.Rmd index d6978ff..92d4d38 100644 --- a/vignettes/seqbio.variant.scoring-variant_scoring.Rmd +++ b/vignettes/KinformR-variant_scoring.Rmd @@ -1,22 +1,22 @@ --- -title: "seqbio.variant.scoring - pedigree-informed rare variant association and penetrance scoring" +title: "KinformR - pedigree-informed rare variant association and penetrance scoring" author: "Cameron M. Nugent" data: "`r Sys.Date()`" output: pdf_document #rmarkdown::html_vignette # vignette: > - %\VignetteIndexEntry{seqbio.variant.scoring-variant_scoring} + %\VignetteIndexEntry{KinformR-variant_scoring} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- ## Introduction -When looking at rare variants within a family, not all affected and unaffected individuals are of equal importance. `seqbio.variant.scoring` is an R package meant to aid in comparative evaluation of information in family-based rare-variant association studies; the package considers evidence of rare variant's association with disease status in a family and scores the variant based on relationships of individuals in a pedigree. Comparing scores across candidates can thereby help in assessing their relative merit. +When looking at rare variants within a family, not all affected and unaffected individuals are of equal importance. `KinformR` is an R package meant to aid in comparative evaluation of information in family-based rare-variant association studies; the package considers evidence of rare variant's association with disease status in a family and scores the variant based on relationships of individuals in a pedigree. Comparing scores across candidates can thereby help in assessing their relative merit. The program leverages Wright’s coefficient of relatedness to score families based on the relationship of individuals as well as their disease status and genotypes for a given variant. A candidate variant is considered strongest when it is shared by an affected individual and other distantly-related affected family members and not shared by closely related unaffected family members. The theory behind this is that more distantly related individuals have a smaller proportion of their genome that is IBD, so the chance of a false positive (shared variant through chance, not due to association with disease) is lower. Conversely, when a closely related relative is unaffected, and the affected and unaffected individuals have different genotypes for the candidate variant, this provides evidence that the disease is not associated with the large IBD portion of the genome shared by the two individuals and thereby gives evidence in favour of the candidate. ```{r loadlib, echo = TRUE, results = 'hide', message=FALSE, warning=FALSE} -library(seqbio.variant.scoring) +library(KinformR) ``` @@ -28,7 +28,7 @@ This input is a matrix containing all the pairwise relationships of individuals The function `read.relation.mat` ```{r} -mat.name1<-system.file('extdata/1234_ex2.mat', package = 'seqbio.variant.scoring') +mat.name1<-system.file('extdata/1234_ex2.mat', package = 'KinformR') rel.mat <- read.relation.mat(mat.name1) rel.mat ``` @@ -42,7 +42,7 @@ Note that the order of individuals can be different between the two files. All i ```{r} -tsv.name1<-system.file('extdata/1234_ex2.tsv', package = 'seqbio.variant.scoring') +tsv.name1<-system.file('extdata/1234_ex2.tsv', package = 'KinformR') status.df <- read.indiv(tsv.name1) status.df