Version 1.0.3

Fixed a bug where a multiqc_data.json file with report_saved_raw_data containing arrays of data would break the parser [#7]

Version 1.0.2

Fixed a bug where a multiqc_data.json file with report_general_stats_data containing arrays of data would break the parser [#7]

Fixed a bug when the plots vector is not provided but sections = "plot" [#5]

Removed the plot_opts key from the load_multiqc function. Instead, the plots are returned as list columns with nested data frames inside the returned data frame. Users are then able to parse out summary statistics using normal dplyr and tidyr functions. Refer to the vignette for examples. Also, instead of selecting plots using the names of this argument, they are selected using the new plots option (documented below) [#1].
Renamed “plots” to “plot” in the sections argument. This ensures consistency with the data frame column names for plots, which are “plot.XX”.
metadata.sample_id is now always the first column in the data frame, even if you have provided a metadata function.

Added list_plots() utility function for listing the available plots [#2].
Added plot_parsers argument to load_multiqc which allows for custom parsers for diverse plot types in MultiQC.
Added plots argument to load_multiqc, which is a vector of plot identifiers to parse.
Created a pkgdown website, which is available at https://multimeric.github.io/TidyMultiqc/.
Added documentation for the plot parsers, which explains the format of the nested data frame produced for each plot type.
Added GitHub repository and issue tracker to package metadata [#3].

Fixed errors when the data frame contains no data (for example because you only requested a single plot which isn’t present) [#2].