- Fixed a bug where a
multiqc_data.json
file withreport_saved_raw_data
containing arrays of data would break the parser [#7]
- Fixed a bug where a
multiqc_data.json
file withreport_general_stats_data
containing arrays of data would break the parser [#7]
- Fixed a bug when the
plots
vector is not provided butsections = "plot"
[#5]
- Removed the
plot_opts
key from theload_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 normaldplyr
andtidyr
functions. Refer to the vignette for examples. Also, instead of selecting plots using the names of this argument, they are selected using the newplots
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 toload_multiqc
which allows for custom parsers for diverse plot types in MultiQC. - Added
plots
argument toload_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].