c(person("Cristina", "Tortora", role = c("aut", "cre","cph"), email = "grikris1@gmail.com", comment = c(ORCID = "0000-0001-8351-3730")),
person("Antonio", "Punzo", role = c("aut"), comment = c(ORCID = "0000-0001-7742-1821")),
person("Louis", "Tran", role = c("aut")))
Model based clustering using
the multivariate multiple Scaled t (MST) and multivariate multiple
scaled contaminated normal (MSCN) distributions. The MST is an
extension of the multivariate Student-t distribution to include
flexible tail behaviors, Forbes, F. & Wraith, D. (2014) <doi:10.1007/s11222-013-9414-4>. The MSCN represents a  heavy-tailed
generalization of the multivariate normal (MN) distribution to
model elliptical contoured scatters in the presence of mild outliers
(also referred to as "bad" points) and automatically detect bad points, Punzo, A. & Tortora, C. (2021) <doi:10.1177/1471082X19890935>.
gtools, Matrix, mclust, mnormt, mvtnorm, psych, cluster,
ggplot2, GGally
Cristina Tortora [aut, cre, cph]
(<https://orcid.org/0000-0001-8351-3730>),
Antonio Punzo [aut] (<https://orcid.org/0000-0001-7742-1821>),
Louis Tran [aut]

Combine Data from Positive and Negative Ionization Mode Finding
Common Entities
Find common entities detected in both positive and negative
ionization mode, delete this entity in the less sensible mode and combine both
matrices.

Preprocessing of Gas Chromatography-Mass Spectrometry (GC-MS)
data
Elodie Courtois, Yann Guitton, Florence Nicole
Package for the detection of molecules in complex mixtures
of compounds. It creates an initial data matrix from several
GC-MS analyses by collecting and assembling the information
from chromatograms and mass spectra (MS.DataCreation). It tests
for the best unsupervised clustering method to group similar
mass spectra into molecules (MS.test.clust). It runs the
optimal unsupervised clustering method on the initial data
matrix, identifies the optimal number of clusters, produces
different files for facilitating the identification of
molecules and returns fingerprinting or profiling matrices
(MS.clust).