Provides a novel visualization technique for plotting timestamped events
    on a 24-hour circular clock face. This is particularly useful for analyzing
    daily patterns, event clustering, and gaps in temporal data. The package
    also generalizes this approach to create cyclic charts for other periods,
    including weekly and monthly cycles, enabling effective event planning and
    pattern analysis across multiple time frames.

A set of functions to fit a boosting conditional logit model.

Tools for the fitting and cross validation of exact conditional logistic regression models with lasso and elastic net penalties. Uses cyclic coordinate descent and warm starts to compute the entire path efficiently.

Quickly estimate the net growth rate of a
    population or clone whose growth can be approximated by a birth-death
    branching process.  Input should be phylogenetic tree(s) of clone(s) with
    edge lengths corresponding to either time or mutations. Based on
    coalescent results in Johnson et al. (2023) <doi:10.1093/bioinformatics/btad561>. Simulation
    techniques as well as growth rate methods build on prior work from
    Lambert A. (2018) <doi:10.1016/j.tpb.2018.04.005> and Stadler T. (2009)
    <doi:10.1016/j.jtbi.2009.07.018>.

Defines the classes and functions used to simulate and
  to analyze data sets describing copy number variants and,
  optionally, sequencing mutations in order to detect clonal subsets.
  See Zucker et al. (2019) <doi:10.1093/bioinformatics/btz057>.

Analyze data from next-generation sequencing experiments on genomic samples. 'CLONETv2' offers a set of functions to compute allele specific copy number and clonality from segmented data and SNPs position pileup. The package has also calculated the clonality of single nucleotide variants given read counts at mutated positions. The package has been developed at the laboratory of Computational and Functional Oncology, Department of CIBIO, University of Trento (Italy), under the supervision of prof Francesca Demichelis. References: Prandi et al. (2014) <doi:10.1186/s13059-014-0439-6>; Carreira et al. (2014) <doi:10.1126/scitranslmed.3009448>; Romanel et al. (2015) <doi:10.1126/scitranslmed.aac9511>.