Function reference • moanin

Datasets
Working with functions and splines How to represent your time-course data with functions and work with them.
`create_moanin_model(<DataFrame>)` `create_moanin_model(<data.frame>)` `create_moanin_model(<matrix>)` `create_moanin_model(<SummarizedExperiment>)`	Class Moanin
`fit_splines()`	Fit splines to each gene of data matrix
`fit_predict_splines()`	Get fitted values for splines for each gene
`plot_splines_data(<Moanin>,<matrix>)` `plot_splines_data(<Moanin>,<numeric>)` `plot_splines_data(<Moanin>,<data.frame>)` `plot_splines_data(<Moanin>,<DataFrame>)` `plot_splines_data(<Moanin>,<missing>)`	Plotting splines
Differential expression analysis on timecourse data Functions to perform week-by-week and overall differential expression analysis.
`DE_timecourse(<Moanin>)`	Run spline models and test for DE of contrasts.
`DE_timepoints(<Moanin>)` `create_timepoints_contrasts(<Moanin>)`	Fit weekly differential expression analysis
`estimate_log_fold_change(<Moanin>)`	Estimates log fold change
Clustering
`splines_kmeans(<Moanin>)`	Performs splines clustering using K-means
`splines_kmeans_predict(<Moanin>)` `splines_kmeans_score_and_label(<Moanin>)`	Assign score and labels from raw data
`plot_cdf_consensus()` `get_auc_similarity_scores()` `plot_model_explorer()`	Evaluate the consensus between sets of clusterings
`consensus_matrix()`	Compute consensus matrix from labels
Downstream analyis
`find_enriched_go_terms()` `create_go_term_mapping()`	Find enriched GO terms
Miscellenaous
`pvalues_fisher_method()`	Fisher's method to combine pvalues
`expression_filtering()`	Utility function to filter out low-expressed genes