Imports: vegan, parallel, doParallel, foreach, gplots, ineq
Suggests: stats, utils, graphics, grDevices, knitr, rmarkdown, pander

Description: Methods for advanced analysis of B cell receptor repertoire
data, like gene usage, mutations, clones, diversity, distance measures and
multidimensional scaling and their visualisation.
Imports: vegan, parallel, doParallel, foreach, gplots, ineq, ape,

Title: Projected t-SNE for Batch Correction
Maintainer: Dayne L Filer <dayne.filer@gmail.com>
Description: Implements the projected t-SNE method for batch correction of
high-dimensional data. Please see Aliverti et al. (2020)
Imports: stats, RSpectra, utils, Rtsne, graphics
Suggests: data.table, batchelor, kBET, splatter, scater, knitr, lisi,

Imports: stats, RSpectra, utils, Rtsne, graphics, splatter
Suggests: data.table, batchelor, kBET, scater, knitr, lisi, harmony,

Title: Bias Corrected Bootstrap Confidence Intervals
Description: Computation of bootstrap confidence intervals in an almost automatic fashion.

Description: Computation of bootstrap confidence intervals in an almost automatic fashion as described in Efron and Narasimhan (2020, <doi:10.1080/10618600.2020.1714633>).

c(person("Ângelo", "Santanna", role = "aut",
person("Daniel", "Cerqueira", role = c("aut", "cre"),
person("Luca", "Scrucca", role = c("ctb"),
Description: Applies beta control charts to defined values, using 'qcc' package with new beta control limits. The Beta Chart presents the control limits based on the Beta probability distribution. Can be used for monitoring fraction data from Binomial distribution as replacement of the p-Charts. The Beta Chart was applied for monitoring the variables in three real studies, and it was compared to the control limits with three schemes. The comparative analysis showed that: (i) Beta approximation to the Binomial distribution was more appropriate with values confined in the [0, 1]- interval; and (ii) the charts proposed were more sensitive to the average run length (ARL), in both in-control and out-of-control processes monitoring. The Beta Charts outperform the Shewhart control charts analyzed for monitoring fraction data. Ângelo Márcio Oliveira Sant’Anna, Carla Schwengber ten Caten (2012) <doi:10.1016/j.eswa.2012.02.146>.