From 58ce9644f699dcfe29a49fce877568862c7470ec Mon Sep 17 00:00:00 2001
From: Magnus Dehli Vigeland <magnusdv@medisin.uio.no>
Date: Wed, 4 Sep 2024 10:27:54 +0200
Subject: [PATCH] Clean up before CRAN submission

---
 NEWS.md          | 11 +++++------
 R/utils.R        |  2 ++
 data-raw/FORCE.R | 24 ++++++++++++------------
 3 files changed, 19 insertions(+), 18 deletions(-)

diff --git a/NEWS.md b/NEWS.md
index 183d403..26800c2 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -8,25 +8,24 @@
     - a new argument `ids`, which when given restricts the checks to those individuals
     - the output column `LR` is renamed to `GLR` (generalised likelihood ratio)
     - new output column `pedrel` describing (in words) each relationship according to the pedigree. The descriptions are obtained with the **verbalisr** package
-    - estimation of P-values for each pairwise relationship, by parametric bootstrap simulations. This feature is controlled through new arguments `nsim`, `pvalThreshold` and `seed`. By default `nsim = 0`, meaning that no simulations are performed. The P-values are stored in the output column `pval`
+    - estimation of P-values for each pairwise relationship, by parametric bootstrap simulations. This feature is controlled through new arguments `nsim`, `pvalThreshold` and `seed`. By default `nsim = 0`, meaning that no simulations are performed. The P-values are stored in the output column `pval`.
 
 
 * New function `quickLR()` performs the most common kinship tests (paternity and sibship) for a pair of individuals. 
 
-* New function `ibdLoglik()` computes the pairwise likelihood for given set IBD coefficients (kappa or delta). It replaces the previous (unexported) `.IBDlikelihood` and versions of this.
+* New function `ibdLoglik()` computes the pairwise likelihood for given set IBD coefficients (kappa or delta).
 
 * Improved progress bars using the `pbapply` package.
 
 ## Other
 
-* Refresh code in examples.
-* Removed deprecated functions `readFam()` etc, which have been moved to the **pedFamilias** package.
-
 * Removed (long deprecated) `IBDtriangle()`, replaced by `ribd::ibdTriangle()`.
 
 * Improved `missingPersonPlot()` appearance.
 
-* Better removal of missing data in `ibdEstimate()`.
+* In `ibdEstimate()`, more efficient data prep, and better removal of missing data.
+
+* Refresh code in examples.
 
 
 # forrel 1.6.1
diff --git a/R/utils.R b/R/utils.R
index eee8795..f7fef0e 100644
--- a/R/utils.R
+++ b/R/utils.R
@@ -173,6 +173,8 @@ fixAllelesAndFreqs = function(alleles = NULL, afreq = NULL,
 }
 
 
+# TODO: Remove the following
+
 #' Add points to the IBD triangle
 #'
 #' This function is re-exported from the `ribd` package. For documentation see
diff --git a/data-raw/FORCE.R b/data-raw/FORCE.R
index 29b97c9..cf0c4ac 100644
--- a/data-raw/FORCE.R
+++ b/data-raw/FORCE.R
@@ -6,12 +6,12 @@ xraw = readxl::read_xlsx("data-raw/FORCE-data.xlsx",
                          n_max = 5422,  # skip bad ones at the bottom
                          col_types = "text")
 
-x = xraw %>%
-  dplyr::filter(startsWith(Type, "Kinship")) %>%
+x = xraw |>
+  dplyr::filter(startsWith(Type, "Kinship")) |>
   dplyr::select(CHROM = Chromosome, MARKER = SNP, POS = "GRCh38 Region",
-         REF = "Reference Allele", ALT = "Alternate Allele") %>%
-  dplyr::mutate(POS = as.integer(POS)) %>%
-  print
+         REF = "Reference Allele", ALT = "Alternate Allele") |>
+  dplyr::mutate(POS = as.integer(POS)) |>
+  print()
 
 
 mart = useEnsembl(biomart = "snps", dataset = "hsapiens_snp")
@@ -20,19 +20,19 @@ info = getBM(
   filters = c("snp_filter", "chr_name"),
   values = list(x$MARKER, 1:22),
   mart = mart
-) %>% as_tibble() %>% print()
+) |> as_tibble() |> print()
 
 filter(info, minor_allele == "")
 anyDuplicated(info$refsnp_id)
 
-y = left_join(x, info, by = c(MARKER = "refsnp_id")) %>%
-  dplyr::filter(minor_allele != "") %>%
+y = left_join(x, info, by = c(MARKER = "refsnp_id")) |>
+  dplyr::filter(minor_allele != "") |>
   dplyr::mutate(
     MB = POS / 1e6,
     A1 = if_else(minor_allele == REF, ALT, REF),
     A2 = if_else(minor_allele == REF, REF, ALT),
     FREQ1 = 1 - minor_allele_freq
-  ) # %>% print
+  ) # |> print
 
 # Checks
 filter(y, POS != chrom_start)
@@ -40,10 +40,10 @@ filter(y, is.na(FREQ1))
 filter(y, nchar(A1) !=1 | nchar(A2) !=1)
 
 # Final table
-FORCE = y %>%
-  dplyr::select(CHROM, MARKER, MB, A1, A2, FREQ1) %>%
+FORCE = y |>
+  dplyr::select(CHROM, MARKER, MB, A1, A2, FREQ1) |>
   as.data.frame()
 
 print(head(FORCE))
 
-usethis::use_data(FORCE, overwrite = TRUE)
+# usethis::use_data(FORCE, overwrite = TRUE)