karyotapR1.0.2 package

DNA Copy Number Analysis for Genome-Wide Tapestri Panels

assayBoxPlot

Generate a box plot from assay data

assayHeatmap

Generate heatmap of assay data

calcCopyNumber

Calculate relative copy number value for each cell-probe unit using re...

calcGMMCopyNumber

Call copy number for each cell-chromosome using Gaussian mixture model...

calcNormCounts

Normalize raw counts

calcSmoothCopyNumber

Smooth copy number values across chromosomes and chromosome arms

callSampleLables

Call sample labels based on feature counts

corner

Print the top-left corner of a matrix

countBarcodedReads

Get read counts from barcoded reads

CreateTapestriExperiment

Create TapestriExperiment object from Tapestri Pipeline output

getChrOrder

Get chromosome order from a string of chromosome/contig names

getCytobands

Add chromosome cytobands and chromosome arms to TapestriExperiment

getGMMBoundaries

Calculate decision boundaries between components of copy number GMMs

getTidyData

Get tidy-style data from TapestriExperiment objects

karyotapR-package

karyotapR: DNA Copy Number Analysis for Genome-Wide Tapestri Panels

moveNonGenomeProbes

Move non-genome probes counts and metadata to altExp slots

newTapestriExperimentExample

Create Example TapestriExperiment

PCAKneePlot

Plot of PCA proportion of variance explained

plotCopyNumberGMM

Plot copy number GMM components

reducedDimPlot

Scatter plot for dimensional reduction results

runClustering

Cluster 2D data

runPCA

Cluster assay data by Principal Components Analysis

runUMAP

Cluster matrix data by UMAP

slotGettersSetters

Getter and Setter functions for TapestriExperiment slots

TapestriExperiment-class

TapestriExperiment Class Definition

Analysis of DNA copy number in single cells using custom genome-wide targeted DNA sequencing panels for the Mission Bio Tapestri platform. Users can easily parse, manipulate, and visualize datasets produced from the automated 'Tapestri Pipeline', with support for normalization, clustering, and copy number calling. Functions are also available to deconvolute multiplexed samples by genotype and parsing barcoded reads from exogenous lentiviral constructs.

  • Maintainer: Joseph Mays
  • License: MIT + file LICENSE
  • Last published: 2025-11-01