Package index • APL

All functions

apl(): Association Plot

apl_coords(): Calculate Association Plot coordinates

apl_ggplot(): Plot Association Plot with ggplot

apl_plotly(): Plot Association Plot with plotly

apl_score(): Find rows most highly associated with a condition

apl_topGO(): Run Gene overrepresentation analysis with topGO

as.cacomp(): Create cacomp object from Seurat/SingleCellExperiment container

as.list(<cacomp>): Convert cacomp object to list.

ca_3Dplot(): Plot of the first 3D CA projection of the data.

ca_biplot(): Plot of 2D CA projection of the data.

ca_coords(): Calculate correspondence analysis row and column coordinates.

new_cacomp(): An S4 class that contains all elements needed for CA.

cacomp(): Correspondance Analysis

cacomp_names(): Prints slot names of cacomp object

cacomp_slot(): Access slots in a cacomp object

calc_residuals(): Calculate residuals for Correspondence analysis

check_cacomp(): Check if cacomp object was correctly created.

clip_residuals(): Perform clipping of residuals

comp_NB_residuals(): Compute Negative-Binomial residuals

comp_ft_residuals(): Compute Freeman-Tukey residuals

comp_std_residuals(): Compute Standardized Residuals

elbow_method(): Runs elbow method

inertia_rows(): Find most variable rows

is.empty(): Helper function to check if object is empty.

permutation_cutoff(): Calculates permuted association plot coordinates

pick_dims(): Compute statistics to help choose the number of dimensions

plot_enrichment(): Generates plot for results from apl_topGO

random_direction_cutoff(): Random direction association plot coordinates

recompute(): Recompute missing values of cacomp object.

rm_zeros(): removes 0-only rows and columns in a matrix.

run_APL() runAPL(): Compute and plot Association Plot

run_cacomp(): Internal function for `cacomp`

scree_plot(): Scree Plot

show.cacomp() show(<cacomp>): Prints cacomp object

subset_dims(): Subset dimensions of a caobj

var_rows(): Find most variable rows