Provides R functions for calculating basic effect size indices for 
  single-case designs, including several non-overlap measures and parametric 
  effect size measures, and for estimating the gradual effects model developed 
  by Swan and Pustejovsky (2018) <DOI:10.1080/00273171.2018.1466681>. 
  Standard errors and confidence intervals (based on the assumption that the outcome 
  measurements are mutually independent) are provided for the subset of effect sizes 
  indices with known sampling distributions.

Creates complex heatmaps for single cell RNA-seq data that simultaneously 
    display gene expression levels (as color intensity) and expression percentages 
    (as circle sizes). Supports gene grouping, cell type annotations, and time point 
    comparisons. Built on top of 'ComplexHeatmap' and integrates with 'Seurat' objects.
    For more details see Gu (2022) <doi:10.1002/imt2.43> and Hao (2024) <doi:10.1038/s41587-023-01767-y>.

One key exploratory analysis step in single-cell genomics data analysis
    is the prediction of features with different activity levels. For example, we want 
    to predict differentially expressed genes (DEGs) in single-cell RNA-seq data, 
    spatial DEGs in spatial transcriptomics data, or differentially accessible 
    regions (DARs) in single-cell ATAC-seq data. 'singleCellHaystack' predicts differentially
    active features in single cell omics datasets without relying on the clustering
    of cells into arbitrary clusters. 'singleCellHaystack' uses Kullback-Leibler 
    divergence to find features (e.g., genes, genomic regions, etc) that are active
    in subsets of cells that are non-randomly positioned inside an input space (such as 
    1D trajectories, 2D tissue sections, multi-dimensional embeddings, etc). For 
    the theoretical background of 'singleCellHaystack' we refer to our original paper
    Vandenbon and Diez (Nature Communications, 2020) <doi:10.1038/s41467-020-17900-3>
    and our update Vandenbon and Diez (Scientific Reports, 2023) <doi:10.1038/s41598-023-38965-2>.