cnr: cnr: copy number, rounded

cnrR Documentation

cnr: copy number, rounded


The cnr object is a list of four relational matrices. The bins, genes, annotation, qc, chromInfo, and gene.index. The structure is inspired by Scanpy's AnnData which cleverly integrates complex data into a simple architecture.

The object stores processing results required for data exploration, visualization and genetic analyses. Specifically, the distance matrix, phylogenetic analysis, pseudobulk, and heterogeneity analysis.




An object class list containg a rounded CNR

  • X, An integer matrix of bins x n.cells containing copy number estimations for each bin[i] and cell[j] Where bins represent a common genomic segment across all cells (either a fixed with, variable binning, or .seg data). This data can be constructed using a variable length bin and CBS (Varbin algorithm) (Baslan et al 2012.), and implemented on Ginkgo, or from hmmCopy. These are upstream analyses to the package.

    For mutations in single-cells, the cnq can be a binary incidence (0,1) matrix representing presence or absence of specific mutations, or a ternary (0,1,2) representing genotypes as the number of alternate allele copies

    We noticed that estimates for deletions and losses don't follow standard numeric rounding. We set a the thresholds of < 0.2 (average quantal estimate of the Y chromosome in females) for deletions (i.e. 0 copies); between 0.2 and 1.2 for losses (i.e. 1 copy); between 1.2 and 2.5 for 2 copies, and everything else standard numeric rounding.

  • genes, gene copy number interpolation from bins. The genes matrix is an interpolated, transposed, expansion of bins. The expansion is constructed internally using the expand2genes function.

  • Y, phenotypic data of single-cells, contains cells as rows, and phentypes in columns. Phenotypes can be information about individual samples, or if same-cell methods were used, the RNA expression from the same cell.

  • qc, quality control metrics. This matrix contains additional metadata that is technical, e.g. number of reads, MAPD estimates, and the PASS/FAIL qc.status for individual cells. contains cells as rows and metadata as columns

  • chromInfo, ordered chromosome information for the bins

  • gene.index, table to map bins to genes

  • cells, a list of cells

  • bulk, logical, weather the data is bulk DNA or cells. If TRUE, data will not be rounded and it's assumed is log ratio data. If FALSE, data is considered as single-cell and copy numbers are considered as integer copy number. Estimates are rounded to the nearest integer (see above). ...


  • cdb, pairwise cell dissimilarity using Bray-Curtis

  • hcdb, heirarchical clustering of cells based

  • phylo, cell phyogenetic tree. Analysis is produced with ape. Default is "balanced minimum evolution"

  • tree.height, height cutoff of the tree, set as intersection between the total number of multi-cell clusters and one-cell clusters

  • ccp, output from ConsensusClusterPlus, the first element is a color map. Elements 2:(40) contain 4 outputs: consensusMatrix, consensusTree, consensusClass, ml, and clrs. Each element corresponds to k in k-means clustering

  • kStats, spectral analysis of consensus clustering

  • eigenVals, spectral analysis eigen values

  • optK optimumn k-parameter (kCC), and stable K (sK)

  • cluster_heterogeneity, summary metrics of clones/clusters

  • uclust, unique clusters with 3 or more cells

  • DDRC.df, bin pseudobulk profiles of each clone (or other chosen group)

  • DDRC.g, gene pseudobulk profiles

  • vdj.cells list of vdj.cells produced by genotype_vdj

  • DDRC.dist, bray curtis disimilarity of clones

  • DDRC.phylo, phylogenetic analysis of clones


SingerLab/gac documentation built on March 23, 2024, 5:15 a.m.