Package index • wispack

Main

wisp(): Fit wisp to count data

Model functions

wisp.sigmoid(): Wisp sigmoid function, implemented in R

wisp.warp(): Wisp warping function, implemented in R

Analysis functions

analyze.residuals(): Analyze residuals from wisp fit

pvalues.samples(): Compute p-values using ecdf from parameter resamples

sample.stats(): Estimate p-values and confidence intervals from resampled parameters

Plotting functions

plot.MCMC.bs.comparison(): Visually compare normality and autocorrelation of bootstrap and MCMC parameter estimates

plot.MCMC.walks(): Plot sampling of random walks and negative log likelihood from MCMC simulations

plot.decomposition(): Plot individual components of wisp fit for a single species level

plot.effect.dist(): Plot parameter distributions from WISP results as histograms

plot.parameters(): Plot of wisp parameters

plot.ratecount(): Plot fitted model and data

plot.species.summary(): Print rate-count, residual, and parameter plots for one species level together.

plot.timeseries(): Plot timeseries effects from wisp results

demo.sigmoid.plots(): Make plot demonstrating how the wisp function is determined by the Rt, slope, and tpoint parameters

demo.warp.plots(): Make plot demonstrating how the wisp function is warped by the warping factors

MERFISH preprocessing functions

make_count_data(): Load and parse data, HDF5

make_count_data_csv(): Load and parse data, csv

cortical_coordinate_transform(): Function to transform coordinates for each mouse and extract layer boundary estimates

create.count.data.WSPmm(): Function to convert to WSPmm format