nmr_detect_peaks_tune_snr().nmr_autophase() for automated phase correction using the NMRphasing package (#68).to_ASICS function to export dataset for ASICS quantification (#68).ggplot2::qplot()Improved the download_MTBLS242() function, allowing to either download the parts
of MTBLS242 needed for the tutorial or the whole dataset, which may be nice to
have if you want to play beyond the tutorial.
When reading a Bruker sample from a zip file, you now can specify in the file
name the zip subdirectory. For instance, "/path/to/sample.zip!/sample/3", when
sample.zip contains a folder named sample with a subfolder named 3 that
includes the sample data you want to actually read.
fix_baseline = FALSE in nmr_integrate_regions() as default. The former TRUE
approach here did not make much sense if peak boundaries were not perfectly
established.Baseline estimation: We now offer nmr_baseline_estimation() besides
nmr_baseline_removal(). The estimation function computes the baseline and saves it
instead of subtracting it from the signal. This is a better approach because it
lets each step of the pipeline decide whether it makes sense to subtract the baseline
or not. The nmr_baseline_removal() is for now still available, but it will be
deprecated in a future version.
For the baselineThresh argument in nmr_detect_peaks() we now suggest using
nmr_baseline_threshold(dataset, method = "median3mad"). This is more robust than
the former (but still the default) method.
Peak detection and integration: We want to approach the peak detection, clustering an integration in a different way. While the old pipeline still works as expected, we have introduced new arguments to peak detection, with backwards compatible defaults and a peak clustering function. We still provide the vignette with the former workflow, because it is still relevant but we may deprecate it in a future version, once we are confident the changes we are making are robust across several datasets.
Parallellization: We are switching from the future package to BiocParallel,
to better integrate in the Bioconductor ecosystem. In this version, if you use
a different future plan you may get a warning to switch to BiocParallel. In a
future version we will remove our dependency with the (awesome) future package.
names(dataset) <- c("Sample1", "Sample2").axis = NULL is given in nmr_interpolate_1D()nmr_dataset object.future package (#65, thanks to @HenrikBengtsson)plot_interactive now accepts an overwrite argument to avoid asking the user
interactivelynmr_detect_peaks_tune_snr to tune the SNR threshold with the right
other parametersdownload_MTBLS242() function to help download the data for the tutorialnmr_data_analysissave_profiling_plotsnmr_normalize_extra_info
that offers a less confusing name.nmr_identify_regions_cell functionHMDB_cellnmr_identify_regions_blood functionnmr_identify_regions_urine functionHMDB_urinecomputes_peak_width_ppmfunction for nmr_integrate_peak_positionsget_integration_with_metadatanmr_identify_regions functionHMDB_bloodfiles_to_rDolphin functionbrowseVignettes("NIHSnmr").Rename injection_id to NMRExperiment.
nmr_dataset_load and nmr_dataset_save now use readRDS and saveRDS
instead of load and save. This is the right approach to serialize
single R objects. If you need a script to convert previously saved datasets (created
using nmr_dataset_save) please use
NIHSnmr:::nmr_dataset_load_old_and_save("your_old_file.RData", "your_old_file.RDS")
to convert the files. Sorry for the inconvenience, but the sooner we fix this
the better.
filter to select a subset of samples from an nmr_dataset object has
been adapted to dplyr >= 0.7.4. Unless you used the .dots argument in
your calls there is no need to change anything. This means we now use a tidy
evaluation syntax for filter.
nmr_get_metadata() returns always a data frame / tibble, even when only a single
column is requested. It also always includes the "NMRExperiment" column.
nmr_dataset object has two tables metadata and metadata_ext. The
metadata_ext table includes all the metadata we add with nmr_add_metadata while
metadata has the internal metadata (acquisition parameters, etc).
Please use nmr_get_metadata(nmr_dataset) instead of nmr_dataset$metadata.
Remove workaround to dplyr issue: https://github.com/tidyverse/dplyr/issues/2203 (Sergio Oller reported and fixed the issue, dplyr-0.7.0 is fixed)
The Bruker title file has quite a free format definition. A title file can contain lines like "Field value" or "Field value ;" or simply "value". The heuristics to parse the title file have been improved.
Depend on tidyr 0.8.1. tidyr 0.8.0 had a bug that we reported (and for which we also provided a fix): https://github.com/tidyverse/tidyr/pull/419
nmr_get_metadata gives a warning if the user asks for metadata columns that
are missing.
New nmr_integrate_regions function.
nmr_normalize accepts pqn normalization.