Statistics
It is often useful to summarize spectral data before plotting, and that is what these transformations do.

stat_peaks() stat_valleys()

Local maxima (peaks) or minima (valleys) 
stat_poly_eq()

Equation, pvalue, R^2, AIC or BIC of fitted polynomial 
stat_fit_tb()

Modelfit summary or ANOVA 
stat_fit_tidy()

One row data frame with fitted parameter estimates 
stat_fit_glance()

One row summary data frame for a fitted model 
stat_fit_augment()

Augment data with fitted values and statistics 
stat_fit_deviations()

Residuals from model fit as segments 
stat_fit_residuals()

Residuals from a model fit 
stat_dens2d_filter() stat_dens2d_filter_g()

Filter observations by local density 
stat_dens2d_labels()

Reset labels of observations in high density regions 
stat_quadrant_counts()

Number of observations in quadrants 
stat_fmt_tb()

Select and slice a tibble nested in data 