Package index • fastCNV

Main Functions

Core functions for CNV analysis

fastCNV(): Fast CNV Detection for Single-Cell and Spatial Transcriptomics Data

fastCNV_10XHD(): fastCNV_10XHD calls all of the internal functions needed to compute the putative CNV on a Seurat Visium HD object or a list of Seurat Visium HD objects

CNVAnalysis(): CNVAnalysis Runs Copy Number Variation (CNV) analysis on a Seurat object or a list of Seurat objects.

CNVCalling(): CNVCalling Performs Copy Number Variation (CNV) analysis on a Seurat object.

CNVCallingList(): CNVCalling for a List of Seurat Objects Performs Copy Number Variation (CNV) analysis on a list of Seurat objects.

Clustering & Classification

Functions for identifying CNV subpopulations

CNVCluster(): Perform CNV Clustering with Seurat Object

CNVClassification(): CNV Classification Classifies the CNV results into loss, gain, or no alteration for each observation and chromosome arm.

mergeCNVClusters(): Merge CNV Clusters in a Seurat Object

CNVPerChromosomeArm(): CNV Per Chromosome Arm Computes the CNV fraction of each spot/cell per chromosome arm, then stores the results into the metadata.

Phylogenetic Analysis

Functions for clonal tree construction

CNVTree(): Build, annotate and plot a Phylogenetic Tree from a seurat Object containing the CNV results from fastCNV()

buildCNVTree(): Construct a Phylogenetic Tree from a Copy Number Variation (CNV) Matrix

annotateCNVTree(): Annotate a Phylogenetic Tree with CNV Events

generateCNVClonesMatrix(): Generate CNV Matrix for CNV Clusters by Chromosome Arm

Visualization

Plotting functions

plotCNVResults(): Plot CNV Results into a Heatmap Builds a heatmap to visualize the CNV results based on genomic scores.

plotCNVResultsHD(): Plot Visium HD CNV Results into a Heatmap Builds a heatmap to visualize the Visium HD CNV results based on genomic scores.

plotCNVTree(): Plot an Annotated Phylogenetic Tree with CNV Events

Data Preparation

Helper functions for data processing

prepareCountsForCNVAnalysis(): Aggregate Observations by Cell Type for CNV Analysis Aggregates observations with the same cell types to increase counts per observation, improving Copy Number Variation (CNV) computation.

getGenes(): Download Gene Information from Ensembl

annotations8umTo16um(): Project 8µm Spatial Annotation onto 16µm Spots

Data

Built-in datasets

geneMetadata: Genes Data from Ensembl Version 113

Utilities

Internal utility functions

classifyCNV(): CNV Classification for a Given Vector Classifies each CNV value in a vector as "loss", "gain", or "no alteration" based on specified thresholds.

computeAverageExpression(): Compute average expression for patients