Ran usethis::use_package_doc()

NEWS.md

@@ -10,8 +10,12 @@ I think I encountered a situation where 4-96 was not enough so I've bumped it to
 This may have been addressed at 64a308ba50b9119108e8946737460de5997b805b by adding `samples` to vcfR method `[`.
 * In issue #92 (vcfR2genlight big data #92), JimWhiting91 has documented that `extract.gt()` could be greatly improved with multithreading. While he used `mclapply()` I do not feel this is the best solution because it does not work on Windows. I think a better solution would be [RCppParallel](https://rcppcore.github.io/RcppParallel/) because this should work on all CRAN platforms.
 
+# vcfR 1.15.0
+Released on CRAN 2023-XX-XX
+* Ran usethis::use_package_doc()
+
 # vcfR 1.14.0
-Released on CRAN 202X-XX-XX
+Released on CRAN 2023-02-10
 * Compile time 'nodiscard' attribute: changed 'col_vec.size()' to 'sizeof(col_vec)' in ad_frequency.cpp and masplit.cpp
 * vcfR_to_tidy handles no INFO in meta
 

R/vcfR-package.R

@@ -0,0 +1,6 @@
+#' @keywords internal
+"_PACKAGE"
+
+## usethis namespace: start
+## usethis namespace: end
+NULL

R/vcfR.R

@@ -40,8 +40,8 @@
 #' @import pinfsc50
 #' @import ape
 #' @docType package
-#' @name vcfR
-#' @rdname vcfR
+#' @name vcfR-package
+# ' @rdname vcfR
 #' @useDynLib vcfR, .registration = TRUE
 #' @importFrom Rcpp sourceCpp
 #' @importFrom stats setNames

R/vcfR_to_tidy_functions.R

@@ -17,7 +17,8 @@
 #' with very large data sets, they provide a good framework for handling and filtering
 #' large variant data sets.  For some background
 #' on the benefits of such "tidy" data frames, see 
-#' \doi{doi.org/10.18637/jss.v059.i10}{this article}.
+#' \doi{doi.org/10.18637/jss.v059.i10}.
+# ' \doi{doi.org/10.18637/jss.v059.i10}{this article}.
 # ' \href{https://doi.org/10.18637/jss.v059.i10}{this article}.
 # ' \href{https://www.jstatsoft.org/article/view/v059i10}{this article}.
 #'