Function reference • sSNAPPY

Functions for deriving single-sample pathway perturbation scores
`weight_ss_fc()`	Compute weighted single sample LogFCs from normalised logCPM
`retrieve_topology()`	Retrieve pathway topology as weighted adjacency matrix
`raw_gene_pert()`	Compute Gene-wise Perturbation Score
`pathway_pert()`	Compute Single-sample Pathway-level Perturbation Score
`rank_gene_pert()`	Rank genes by perturbation scores within each sample
`generate_permuted_scores()`	Permute sample labels to simulate null distribution of perturbation scores
`normalise_by_permu()`	Normalise test perturbation scores by permutation results
Visualisation Functions
`plot_gs_network()`	Plot significantly perturbed gene-sets as a network
`plot_gene_contribution()`	Plot genes' contribution to a specific pathway's perturbation as heatmap
`plot_community()`	Visualise the community structure in significantly perturbed gene-set network
`plot_gs2gene()`	Plot pathways and genes contained in them as a network
Data Objects
`logCPM_example`	logCPM_example: Normalised logCPM of patient-derived explant models obtained from 5 ER-positive primamry breast cancer patients (GSE80098)
`metadata_example`	metadata_example: Sample metadata for malignant breast cancer tumours PDE from 5 ER+ breast cancer patients (GSE80098)
`gsAnnotation_df`	gsAnnotation_df: Categorization of KEGG pathways used for community annotation
Package
`sSNAPPY`	sSNAPPY: A package for testing directional single sample pathway perturbation

Reference