We developed a lightweight machine learning tool for RNA profiling of acute lymphoblastic leukemia (ALL), however, it can be used for any problem where multiple classes need to be identified from multi-dimensional data. The methodology is described in Makinen V-P, Rehn J, Breen J, Yeung D, White DL (2022) Multi-cohort transcriptomic subtyping of B-cell acute lymphoblastic leukemia, International Journal of Molecular Sciences 23:4574, <doi:10.3390/ijms23094574>. The classifier contains optimized mean profiles of the classes (centroids) as observed in the training data, and new samples are matched to these centroids using the shortest Euclidean distance. Centroids derived from a dataset of 1,598 ALL patients are included, but users can train the models with their own data as well. The output includes both numerical and visual presentations of the classification results. Samples with mixed features from multiple classes or atypical values are also identified.

person("Stéphane", "Laurent", email = "laurent_step@outlook.fr", role = c("aut", "cre"))
Computation of the alpha hull of a set of points in the 3D
space, that is to say "something like the shape formed by these
points". The alpha hull depends on a positive parameter alpha. When
alpha goes to zero, the alpha hull degenerates to the set of points,
while it is the convex hull of the set of points when alpha goes to
infinity. Computations are performed by the 'CGAL' 'C++' library
<https://www.cgal.org/>.

Partition/Decomposition of Additive Genetic Values by Paths of
Information
Additive genetic (breeding) value represents a sum of additive gene effects over whole genome and can be inferred from phenotype values of relatives via pedigree based mixed models. The partitioning method is described in Garcia-Cortes et al. (2008) <DOI:10.1017/S175173110800205X>.
RColorBrewer (>= 1.0-2), truncnorm (>= 1.0-5), knitr,
rmarkdown, testthat

Partition/Decomposition of Breeding Values by Paths of
Information
A software that implements a method for partitioning genetic trends to
quantify the sources of genetic gain in breeding programmes.
The partitioning method is described in Garcia-Cortes et al.
(2008) <doi:10.1017/S175173110800205X>. The package includes the
main function AlphaPart for partitioning breeding values and auxiliary
functions for manipulating data and summarizing, visualizing, and saving
results.