v1.0.7

• This is the latest release, submitted to CRAN on 03. July.2024

v1.0.6

• This is the latest release, submitted to CRAN on 22. January 2024

Full Changelog: v1.0.5...v1.0.6

v1.0.5

• Bugfix: Wrong indexing in choose-optimal-reference always picked the first sample as a reference. Thanks to hebertodelrio for pointing this out!

v1.0.4

• Increased speed when setting max_diff_peak2mean = 0:
  In this special case there is no need to use a time-consuming iterative approach to align peaks. Instead, peaks are simply sorted in temporal order of absolute retention time values. This is implemented in two steps. (1) Across all samples, unique retention times are extracted, sorted in increasing temporal order and written to a template data frame (number of rows equals number of unique retention times). (2) For each sample, peaks are matched to the corresponding row of the template data frame. Note, in this situation only the parameter min_diff_peak2peak determines which peaks are considered as potentially homologous.
• Small bug fixed that caused problems when plotting x-axis labels in gc_heatmap.
• Added a test for detecting inconsistently ordered retention times. In general, retention times should appear in increasing temporal order. If this assumption is violated, retention times are reordered and a warning message is shown.

v1.0.3

Aside a few minor changes, including minor changes in the documentation and check functions, this version includes the following changes:

• Added fill = TRUE as a parameter in utils::read.table when reading data from text within internal functions. Loading GC data with utils::read.table failed in cases of missing values in a column (i.e. empty). This is the correct behaviour as missing data should always be coded explicitly by 'NA' or removed from the dataset before
• Added a new boolean parameter remove_empty for the main function align_chromatograms. If samples are empty (ie. no peak) this parameter allows to remove those cases from the dataset to avoid problems in post-hoc analyses. By default FALSE, ie. all but the blank samples are kept.
• Added a new boolean parameter permute for the functions align_chromatograms and align_peaks. This allows to change the default behaviour of random permutation of samples during the alignment and might be useful if exact replication is needed.

CRAN release GCalignR 1.0.2

Citation to our paper added:
Ottensmann M., Stoffel MA, Nichols HJ. & Hoffman JI. (2018). GCalignR: An R package for aligning
gas-chromatography data for ecological and evolutionary studies. PLOS ONE 13(6): e0198311
doi:10.1371/journal.pone.0198311

CRAN release GCalignR 1.0.1

Bugfixes

• A bugfix was applied for handling multiple blanks correctly.
• Progressbars are removed in non-interactive R sessions

Beta release

• A small bug was fixed that caused sometimes issues while handling multiple blanks

Release GCalignR 1.0.0

GCalignR 1.0.0 is the current CRAN release

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Changes since release 0.1.0

New functions are implemented

• choose_optimal_reference offers an automatism to pick suitable references.
• draw_chromatograms allows to represent a peak list in form of chromatogram.
• remove_blanksallows to get rid of peaks that represent contamination after aligning a dataset
• remove_singletons allows to remove single peaks from the dataset after aligning
• merge_redundant_rows allows to merge rows that were not recognised as redundant during the alignment by increasing the threshold value for the evaluation of similarity

Algorithm

• Using pbapply, we implemented progress bars to inform the user about the progress and the estimated running time of intermediate steps in the alignment of peak lists.
• By implementing more efficient code, we were able to speed up the processing, especially picking references is faster by an order of magnitude.

Full alignment of peaks

• Retention times are not rounded to two decimals anymore. Calculations still capture a precision of two decimals for computational reasons.
• Within the aligned results, retention times correspond to the input values. Linear adjustments are only used internally and are documented within the Logfile accessible in the output.

Reference selection

• Reference samples that are used for the coarse alignment of retention times can be picked using a novel algorithm that determines the average similarity across the dataset.

warning messages

• Warnings addressing formatting issues are now more explicit and partly rephrased to avoid ambiguity.

Plots

• Added horizontal axis to barplots summarising peak numbers in plot.GCalign.
• Changed to more prominent colours in binary heatmaps with gc_heatmap.
• The function draw_chromatograms was added as another visualisation tool.

Vignette

• We included a second vignette that explains the algorithm and the supported data in detail.

Documentation

• Helpfiles were rewritten to enhance clarity.

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Release GCalignR 0.1.0

Release GCalignR 0.1.0
https://cran.r-project.org/package=GCalignR