From 117c28163cc604e6439fc561b90725f16b29c90e Mon Sep 17 00:00:00 2001 From: knausb Date: Fri, 1 Dec 2023 14:51:08 -0800 Subject: [PATCH] Ran usethis::use_package_doc() --- NEWS.md | 6 +++++- R/vcfR-package.R | 6 ++++++ R/vcfR.R | 4 ++-- R/vcfR_to_tidy_functions.R | 3 ++- man/{vcfR.Rd => vcfR-package.Rd} | 34 +++++++++++++++++++++++++++++--- man/vcfR_to_tidy_conversion.Rd | 2 +- 6 files changed, 47 insertions(+), 8 deletions(-) create mode 100644 R/vcfR-package.R rename man/{vcfR.Rd => vcfR-package.Rd} (54%) diff --git a/NEWS.md b/NEWS.md index c28ba437..c16aed42 100644 --- a/NEWS.md +++ b/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 diff --git a/R/vcfR-package.R b/R/vcfR-package.R new file mode 100644 index 00000000..a65cf643 --- /dev/null +++ b/R/vcfR-package.R @@ -0,0 +1,6 @@ +#' @keywords internal +"_PACKAGE" + +## usethis namespace: start +## usethis namespace: end +NULL diff --git a/R/vcfR.R b/R/vcfR.R index 13df27b3..ceb77d27 100644 --- a/R/vcfR.R +++ b/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 diff --git a/R/vcfR_to_tidy_functions.R b/R/vcfR_to_tidy_functions.R index 631b9f33..149c14a9 100644 --- a/R/vcfR_to_tidy_functions.R +++ b/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}. #' diff --git a/man/vcfR.Rd b/man/vcfR-package.Rd similarity index 54% rename from man/vcfR.Rd rename to man/vcfR-package.Rd index 030b86da..45ccf432 100644 --- a/man/vcfR.Rd +++ b/man/vcfR-package.Rd @@ -1,10 +1,13 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/vcfR.R +% Please edit documentation in R/vcfR-package.R, R/vcfR.R \docType{package} -\name{vcfR} +\name{vcfR-package} \alias{vcfR} -\title{Variant call format files processed with vcfR.} +\alias{vcfR-package} +\title{vcfR: Manipulate and Visualize VCF Data} \description{ +Facilitates easy manipulation of variant call format (VCF) data. Functions are provided to rapidly read from and write to VCF files. Once VCF data is read into R a parser function extracts matrices of data. This information can then be used for quality control or other purposes. Additional functions provide visualization of genomic data. Once processing is complete data may be written to a VCF file (*.vcf.gz). It also may be converted into other popular R objects (e.g., genlight, DNAbin). VcfR provides a link between VCF data and familiar R software. + vcfR provides a suite of tools for input and output of variant call format (VCF) files, manipulation of their content and visualization. } \details{ @@ -33,5 +36,30 @@ Several example \strong{datasets} are included in vcfR. The \href{https://cran.r-project.org/package=pinfsc50}{pinfsc50} dataset is available as a separate package and includes VCF, GFF and FASTA data for testing and benchmarking. } \seealso{ +Useful links: +\itemize{ + \item \url{https://github.com/knausb/vcfR} + \item \url{https://knausb.github.io/vcfR_documentation/} +} + + More documentation for vcfR can be found at the \href{https://knausb.github.io/vcfR_documentation/}{vcfR documentation} website. } +\author{ +\strong{Maintainer}: Brian J. Knaus \email{briank.lists@gmail.com} (\href{https://orcid.org/0000-0003-1665-4343}{ORCID}) + +Authors: +\itemize{ + \item Niklaus J. Grunwald \email{grunwaln@science.oregonstate.edu} (\href{https://orcid.org/0000-0003-1656-7602}{ORCID}) +} + +Other contributors: +\itemize{ + \item Eric C. Anderson \email{eric.anderson@noaa.gov} (\href{https://orcid.org/0000-0003-1326-0840}{ORCID}) [contributor] + \item David J. Winter \email{david.winter@gmail.com} [contributor] + \item Zhian N. Kamvar \email{zkamvar@gmail.com} (\href{https://orcid.org/0000-0003-1458-7108}{ORCID}) [contributor] + \item Javier F. Tabima \email{caifaz01@gmail.com} (\href{https://orcid.org/0000-0002-3603-2691}{ORCID}) [contributor] +} + +} +\keyword{internal} diff --git a/man/vcfR_to_tidy_conversion.Rd b/man/vcfR_to_tidy_conversion.Rd index 943b7f97..389f501f 100644 --- a/man/vcfR_to_tidy_conversion.Rd +++ b/man/vcfR_to_tidy_conversion.Rd @@ -112,7 +112,7 @@ optimized for operation on large data frames, and, though they can bog down 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}. For some filtering operations, such as those where one wants to filter genotypes upon GT fields in combination with INFO fields, or more complex