c(person(given = "Hadley",
family = "Wickham",
role = c("aut", "cre"),
email = "hadley@rstudio.com"),
person(given = "Max",
family = "Kuhn",
role = "aut",
email = "max@rstudio.com"),
person(given = "Davis",
family = "Vaughan",
role = "aut",
email = "davis@rstudio.com"),
person(given = "RStudio",
role = "cph"))
In order to reduce potential package dependencies
and conflicts, generics provides a number of commonly used S3
generics.
Hadley Wickham [aut, cre],
Max Kuhn [aut],
Davis Vaughan [aut],
RStudio [cph]

covr, pkgload, testthat (>= 3.0.0), tibble, withr

c(
person("Hadley", "Wickham", , "hadley@rstudio.com", role = c("aut", "cre")),
person("Max", "Kuhn", , "max@rstudio.com", role = "aut"),
person("Davis", "Vaughan", , "davis@rstudio.com", role = "aut"),
person("RStudio", role = "cph")
)
In order to reduce potential package dependencies and
conflicts, generics provides a number of commonly used S3 generics.

Estimate Gender from Names in Spanish and Portuguese
person(given = "Juan Pablo",
family = "Marin Diaz",
role = c("aut", "cre"),
email = "jpmarindiaz@gmail.com")
Juan Pablo Marin Diaz <jpmarindiaz@gmail.com>
Estimate gender from names in Spanish and Portuguese.
Works with vectors and dataframes. The estimation works not only
for first names but also full names. The package relies on a
compilation of common names with it's most frequent associated
gender in both languages which are used as look up tables for gender
inference.

Get Gene Sets for Gene Enrichment Analysis
Gene sets are fundamental for gene enrichment analysis. The package 'geneset' enables querying
gene sets from public databases including 'GO' (Gene Ontology Consortium. (2004) <doi:10.1093/nar/gkh036>),
'KEGG' (Minoru et al. (2000) <doi:10.1093/nar/28.1.27>),
'WikiPathway' (Marvin et al. (2020) <doi:10.1093/nar/gkaa1024>),
'MsigDb' (Arthur et al. (2015) <doi:10.1016/j.cels.2015.12.004>),
'Reactome' (David et al. (2011) <doi:10.1093/nar/gkq1018>),
'MeSH' (Ish et al. (2014) <doi:10.4103/0019-5413.139827>),
'DisGeNET' (Janet et al. (2017) <doi:10.1093/nar/gkw943>),
'Disease Ontology' (Lynn et al. (2011) <doi:10.1093/nar/gkr972>),
'Network of Cancer Genes' (Dimitra et al. (2019) <doi:10.1186/s13059-018-1612-0>) and
'COVID-19' (Maxim et al. (2020) <doi:10.21203/rs.3.rs-28582/v1>).
Gene sets are stored in the list object which provides data frame of 'geneset' and 'geneset_name'.
The 'geneset' has two columns of term ID and gene ID. The 'geneset_name' has two columns of
terms ID and term description.