A full set of fast data manipulation tools with a tidy
    front-end and a fast back-end using 'collapse' and 'cheapr'.

Read and write PNG images with arrays, rasters, native
    rasters, numeric arrays, integer arrays, raw vectors and indexed
    values.  This PNG encoder exposes configurable internal options
    enabling the user to select a speed-size tradeoff.  For example,
    disabling compression can speed up writing PNG by a factor of 50.
    Multiple image formats are supported including raster, native rasters,
    and integer and numeric arrays at color depths of 1, 2, 3 or 4. 16-bit
    images are also supported. This implementation uses the 'libspng' 'C'
    library which is available from
    <https://github.com/randy408/libspng/>.

Constructs optimal policy trees which provide a rule-based treatment prescription policy.
 Input is covariate and reward data, where, typically, the rewards will be doubly robust reward estimates.
 This package aims to construct optimal policy trees more quickly than the existing 'policytree' package and
 is intended to be used alongside that package.
 For more details see Cussens, Hatamyar, Shah and Kreif (2025) <doi:10.48550/arXiv.2506.15435>.

Finds the critical sample size ("critical point of stability") for a 
    correlation to stabilize in Schoenbrodt and Perugini's definition of 
    sequential stability (see <doi:10.1016/j.jrp.2013.05.009>).

'FASTQC' is the most widely used tool for evaluating the quality of high throughput sequencing data.  
    It produces, for each sample, an html report and a compressed file containing the raw data. 
    If you have hundreds of samples, you are not going to open up each 'HTML' page. 
    You need some way of looking at these data in aggregate. 
    'fastqcr' Provides helper functions to easily parse, aggregate and analyze 
    'FastQC' reports for large numbers of samples. It provides a convenient solution for building 
    a 'Multi-QC' report, as well as, a 'one-sample' report with result interpretations.