## Model fit and check

Contain the fitGam function used to fit the model, as well as functions to check the fit, extract components and decide on the appropriate number of knots.

fitGAM()

fitGAM

evaluateK()

Evaluate the optimal number of knots required for fitGAM.

nknots()

knots

getSmootherPvalues()

Get smoother p-value as returned by mgcv.

getSmootherTestStats()

Get smoother Chi-squared test statistics.

## Tests

All tests currently implemented in tradeSeq. All tests are of the form xxxTest. Tests can either be run in an omnibus fashion (all lineages) or on an individual basis (lineages for within-lineage tests, and pairwise form between-lineages tests).

associationTest()

Perform statistical test to check whether gene expression is constant across pseudotime within a lineage

diffEndTest()

Perform statistical test to check for DE between final stages of every lineage.

earlyDETest()

Perform test of early differences between lineages

patternTest()

Assess differential expression pattern between lineages.

startVsEndTest()

Perform statistical test to check for DE between starting point and the end stages of every lineage

## Visualization

Functions to plot the results

plotGeneCount()

Plot gene expression in reduced dimension.

plotSmoothers()

Plot the log-transformed counts and the fitted values for a particular gene along all lineages

## Data

The dataset used in example

gamList

A list of GAM models, used to demonstrate the various tests.

celltype

A vector defining cell types, used in the package vignette.

countMatrix

A count matrix, used in the package vignette.

crv

A SlingshotDataset object, used in the package vignette.

sds

A SlingshotDataset object, used in the package unit tests.

## Clustering

Clustering of gene expression patterns

clusterExpressionPatterns(<SingleCellExperiment>) clusterExpressionPatterns(<list>)

Cluster gene expression patterns.

predictCells()

predictCells

predictSmooth()

predictSmooth