Added st_locate() to help with converting region names to serotrackr’s acceptable region codes. First, the function has an automatic component where it tries to match the user’s region names to those predefined in serotrackr::regions_df. This is an exact case insensitive match that treats accented and unaccented letters the same. The function then produces a report of the user’s unmatched unique region names. In its second component, the function has a dot-dot-dot (ellipsis) argument where region codes can be defined for each unmatched unique region name one by one.
Added an argument to st_aggregate() to generate 95% binomial proportion confidence interval for the seroprevalence estimate.
st_save() replaced save_xlsx(). Apart from a more consistent naming scheme, the new function uses the output of both st_validate() and st_aggregate() functions to fill in as much cells as possible in the Excel template.
Added initial version of st_aggregate() to generate aggregate estimates from validated individual level data.
st_validate() replaced map_cols(). Naming of functions will be more consistent, while trying to avoid namespace conflicts. The new function accepts both columns and single values, checks for required input types (character, numeric, or date), applies several validation rules for each argument, and generates descriptive messages in the console about what parts of data are okay and what parts have issues.
Added validation rules as an internal object. These rules will be used at several stages to check data.
Added website using pkgdown.
Added a logo to the README.md file. It will be used in the pkgdown website too.
serotrackr 0.1.0
Initial release.
Added map_cols() function for mapping columns.
Added clean() function for cleaning and validating data.
Added save_xlsx() function for exporting data into the standard Excel template.
Assays and regions are organized in two nested named lists, so users can take advantage of RStudio to search their assays and regions in a dropdown-like behaviour.
Added documention to the current functions and data objects.
Added sample data to showcase what raw data is expected and how the package handles it.