Changes in version 0.99.0                        

  - Initial Bioconductor submission.
  - Post-acquisition processing of targeted LC-MS/MS lipidomics and
    metabolomics results exported from Waters TargetLynx or Skyline, or
    supplied as a plain sample-by-analyte matrix: peak-matrix assembly,
    S/N and LOD/LOQ filtering, blank filtering, missing-value
    imputation, normalisation, internal-standard and volume adjustment
    of vendor-reported concentrations, and batch correction.
    Chromatographic peak detection, integration and calibration-curve
    fitting are outside its scope.
  - Every step is an exported function operating on a
    struct::DatasetExperiment; a whole workflow can additionally be
    driven from a single YAML config via run_MRManalyzeR().
  - Self-contained HTML data-quality and statistical reports: group
    summaries, PCA, sample x feature heatmaps, volcano plots,
    feature-feature correlations, linear models, and enzyme-activity ion
    ratios.
  - run_MRManalyzeR_combine() merges multiple acquisition panels into a
    single analysis.
  - run_example() runs the full workflow on the bundled example dataset
    (a subset of Kolmert et al. 2018,
    doi:10.1016/j.prostaglandins.2018.05.005).
  - Every processing step is also an exported function operating on a
    struct::DatasetExperiment: read_targetlynx() / read_skyline(),
    assemble_dataset(), filter_blanks(), normalise_matrix(),
    adjust_concentration(), impute_missing() and correct_batch(),
    composed by process_dataset().
  - Per-compound quality metrics (CV_QC, CV_sample and their ratio) are
    written into the dataset's variable_meta.
  - A second bundled dataset, example_synthetic.xlsx (plus the processed
    example_synthetic.RDS), is entirely simulated from a fixed seed: two
    chromatographic batches, per-sample protein amounts and
    reconstitution volumes, and a planted treatment effect on 5 of
    its 20 analytes, so normalisation, concentration adjustment, batch
    correction and the statistics can each be demonstrated against a
    known truth.