knitr, testthat, xcms, MSnbase, plotly, shiny, rmarkdown, DT,
crosstalk
Rdisop, BiocParallel, grDevices, graphics, stats, utils,
methods, animation (>= 2.2.3), RColorBrewer, mixtools,
data.table

Isotope pattern, profile and centroid calculation.
Fast and very memory-efficient calculation of isotope
patterns, subsequent convolution to theoretical envelopes
(profiles) plus valley detection and centroidization or
intensoid calculation. Batch processing, resolution
interpolation, wrapper, adduct calculations and molecular
formula parsing.

Isotope pattern, profile and centroid calculation for mass
spectrometry.
Fast and very memory-efficient calculation of isotope patterns, subsequent convolution to theoretical envelopes (profiles) plus valley detection and centroidization or intensoid calculation. Batch processing, resolution interpolation, wrapper, adduct calculations and molecular formula parsing.

Fast and very memory-efficient calculation of isotope patterns,
subsequent convolution to theoretical envelopes (profiles) plus valley
detection and centroidization or intensoid calculation. Batch processing,
resolution interpolation, wrapper, adduct calculations and molecular
formula parsing.

Isotope Pattern, Profile and Centroid Calculation for Mass
Spectrometry

Fast and very memory-efficient calculation of isotope patterns,
subsequent convolution to theoretical envelopes (profiles) plus valley
detection and centroidization or intensoid calculation. Batch processing,
resolution interpolation, wrapper, adduct calculations and molecular
formula parsing.
Loos, M., Gerber, C., Corona, F., Hollender, J., Singer, H. (2015)
<doi:10.1021/acs.analchem.5b00941>.

Peak picking for high resolution mass spectrometry data
Sequential partitioning, clustering and peak detection of
centroided LC-MS mass spectrometry data (.mzXML). Interactive result and raw
data plot.

Peak Picking for High Resolution Mass Spectrometry Data

person(given = "Tomasz",
family = "Kalinowski",
role = c("aut", "cre"),
email = "kalinowskit@gmail.com")
Provides a small set of functions for managing R environments, with defaults designed to encourage usage patterns that scale well to larger code bases. It provides: import_from(), a flexible way to assign bindings that defaults to the current environment; include(), a vectorized alternative to base::source() that also default to the current environment; and attach_eval() and attach_source(), a way to evaluate expressions in attached environments. Together, these (and other) functions pair to provide a robust alternative to base::library() and base::source().