testthat (>= 2.1.0), covr, knitr, rmarkdown, esquisse,
tidyselect
nomnoml, utils, htmlwidgets, rstudioapi, webshot, styler,
methods, here, lifecycle

Cytometric Diversity Indices from 'FlowJo' Workspaces
Bruno M.S. Wanderley, María Victoria Quiroga, André M. Amado, Fernando Unrein
Concatenates some 'flowWorkspace', 'flowCore', 'vegan' and 'gdata' packages functionalities to import 'FlowJo' workspaces and calculates ecological diversity indices for gated populations, based on two dimensions cytograms.
R (>= 3.0), flowWorkspace, flowCore, vegan

Cytometric Diversity Indices from Gated Data
Bruno M.S. Wanderley, Maria Victoria Quiroga, Andre M. Amado, Fernando Unrein
Uses multidimensional contingency tables to calculate ecological diversity indices for gated populations.
flowWorkspace, flowCore, vegan, ggplot2, grDevices, stats,
utils, gridExtra, graphics, methods

Tracing Information Flow for Inter-Software Comparisons in Mass
Spectrometry-Based Bottom-Up Proteomics
person("Oliver", "Kardell", , "Okdll@gmx.net", role = c("aut", "cre"))
Useful functions to standardize software outputs from ProteomeDiscoverer, Spectronaut, DIA-NN and MaxQuant on precursor, modified peptide and proteingroup level and to trace software differences for identifications such as varying proteingroup denotations for common precursor.
comprehenr, dplyr, ggplot2, magrittr, stringr, tibble, tidyr
data.table, kableExtra, knitr, rmarkdown, testthat (>= 3.0.0)

Tools for characterizing flowering traits
Flowering is an important life history trait of flowering plants. It has been mainly analyzed with respect to flowering onset and duration of flowering. This tools provide some functions to compute the temporal distribution of an flowering individual related to other population members. fCV() measures the temporal variation in flowering. RIind() measures the rank order of flowering for individual plants within a population. SI(), SI2(), SI3(), and SI4() calculate flowering synchrony with different methods.

Forecasts future values of a univariate time series.
Flow field forecasting draws information from an interpolated flow field of the observed time series to incrementally build a forecast.