Methods for High-Dimensional Repeated Measures Data
Calculates the bag
Check for 'limma' availability
COVID-19 Markers Dataset
Calculates the depth median.
Calculation of adjusted confidence intervals
Volcano plot of adjusted confidence intervals
Diagnostic plot for comparison of two correlation matrices.
Plots a gemstone to an interactive graphics device
Detection of global group effect
Specifies grid for the calculation of the halfspace location depths
Calculates the halfspace location depth
Genetic algorithm for generating correlated binary data
Calculates the fence and the loop
netRNA:Network meta-analysis for gene expression data
RepeatedHighDim Package
Detection of global group effect
Calculate lower and upper the bounds for pairwise correlations
Simulating correlated binary variables using the algorithm by Emrich a...
Simulating correlated binary variables using the algorithm by Qaqish (...
Robust COVID-19 Dataset
Robust COVID-19 Markers (02 Trim) Dataset
Robust COVID-19 Markers (03 Trim) Dataset
Robust COVID-19 Markers Dataset
scTC_bpplot: Post-trim breakpoint heatmap for scTrimClust results
Robust COVID-19 CLR Transformation Effects (Internal)
COVID-19 CLR Transformation Marker Effects (Internal)
Robust COVID-19 LogNormalized Effects (Internal)
COVID-19 LogNormalized Marker Effects (Internal)
scTC_trim_effect: Compare scTrimClust trimming against default Seurat ...
scTrimClust: Cluster visualization with alpha hull-based outlier detec...
Calculation of probabilities for binary sequences
ProcessedSingle-Cell Data
Setup of the start matrix
Summary of RHighDim function
A toolkit for the analysis of high-dimensional repeated measurements, providing functions for outlier detection, differential expression analysis, gene-set tests, and binary random data generation.