Functions inserting dynamic scatterplots and grids in documents generated by R2HTML.
GPL version 2 or newer.Copyright statement for ptolemy: http://ptolemy.eecs.berkeley.edu/copyright.htm

Functions inserting dynamic scatterplots and grids in documents generated by R2HTML. To view the applets you must install a Java plugin (http://java.sun.com/products/plugin/). The plot applet is a modified version of PtPlot 5.3 (http://ptolemy.eecs.berkeley.edu/).
GPL version 2 or newer. Copyright statement for ptolemy: http://ptolemy.eecs.berkeley.edu/copyright.htm

Haplotype Trend Regression with eXtra Flexibility (HTRX)
c(
person("Yaoling", "Yang", email = "yaoling.yang@bristol.ac.uk", role = c("aut", "cre"),
comment = c(ORCID = "0000-0003-4905-8097")),
person("Daniel", "Lawson", email = "Dan.Lawson@bristol.ac.uk", role = "aut",
comment = c(ORCID = "0000-0002-5311-6213")))
Detection of haplotype patterns that include single nucleotide polymorphisms (SNPs) and non-contiguous haplotypes that are associated with a phenotype. Methods for implementing HTRX are described in Barrie W, Yang Y, Attfield K E, et al (2022) <doi:10.1101/2022.09.23.509097>.
fastglm, caret, parallel, methods, stats

fastglm, caret, parallel, methods, stats, glmnet

Clustering high throughput sequencing (HTS) data
Andrea Rau, Gilles Celeux, Marie-Laure Martin-Magniette, Cathy Maugis-Rabusseau
This package implements two parameterizations of a Poisson mixture model to cluster observations (e.g., genes) in high throughput sequencing data. Parameter estimation is performed using either the EM or CEM algorithm, and the BIC or ICL criteria are used for model selection (i.e., to choose the number of clusters).

Andrea Rau, Gilles Celeux, Marie-Laure Martin-Magniette, Cathy
Maugis-Rabusseau
This package implements two parameterizations of a Poisson
mixture model to cluster observations (e.g., genes) in high
throughput sequencing data. Parameter estimation is performed
using either the EM or CEM algorithm, and the BIC or ICL
criteria are used for model selection (i.e., to choose the
number of clusters).