c(person("Susanne","Stampf", role=c("cre","aut"), email = "susanne.stampf@usb.ch"))

Detecting, combining and filtering isotope, adduct and homologue
series relations in high-resolution mass spectrometry (HRMS)
data
Screening a HRMS data set for peaks related by (1) isotope
patterns, (2) different adducts of the same molecule and/or (3)
homologue series. The resulting isotopic pattern and adduct
groups can then be combined to so-called components, with
homologue series information attached. Also allows plotting and
filtering HRMS data for mass defects, frequent m/z distances
and components vs. non-components.

Screening a HRMS data set for peaks related by (1) isotope patterns, (2) different adducts of the same molecule and/or (3) homologue series. The resulting isotopic pattern and adduct groups can then be combined to so-called components, with homologue series information attached. Also allows plotting and filtering HRMS data for mass defects, frequent m/z distances and components vs. non-components.

Detecting, Combining and Filtering Isotope, Adduct and Homologue
Series Relations in High-Resolution Mass Spectrometry (HRMS)
Data

Detecting Isotope, Adduct and Homologue Relations in LC-MS Data

Quantized simulation data of isotope pattern centroids
Data sets for isotope pattern grouping of LC-HRMS peaks with package nontarget. Based on a vast set of unique PubChem molecular formulas, quantized (a) m/z, (b) m/z differences, (c) intensity ratios and (d) marker centroids of simulated centroid pairs are listed for different instrument resolutions.

Non-Parametric Concordance Coefficient: A Non-Parametric
Concordance Test
c(
person("Rowan","Kuiper",email="r.kuiper.emc@gmail.com",role=c("cre","aut")),
person("Remco","Hoogenboezem",role=c("aut")),
person("Sjoerd","Huisman",role=c("ctb")),
person("Google Inc.", role=c("cph"),comment="Copyright as mentioned in inst/COPYRIGHTS, applies to the sparse hash library implemented in NOPACO"))
A non-parametric test for multi-observer concordance and
differences between concordances in (un)balanced data.
methods, Matrix (>= 1.1.5), parallel, stats
Rowan Kuiper [cre, aut],
Remco Hoogenboezem [aut],
Sjoerd Huisman [ctb],
Google Inc. [cph] (Copyright as mentioned in inst/COPYRIGHTS, applies
to the sparse hash library implemented in NOPACO)