DOI: 10.18129/B9.bioc.cardelino  

This package is for version 3.16 of Bioconductor; for the stable, up-to-date release version, see cardelino.

Clone Identification from Single Cell Data

Bioconductor version: 3.16

Methods to infer clonal tree configuration for a population of cells using single-cell RNA-seq data (scRNA-seq), and possibly other data modalities. Methods are also provided to assign cells to inferred clones and explore differences in gene expression between clones. These methods can flexibly integrate information from imperfect clonal trees inferred based on bulk exome-seq data, and sparse variant alleles expressed in scRNA-seq data. A flexible beta-binomial error model that accounts for stochastic dropout events as well as systematic allelic imbalance is used.

Author: Jeffrey Pullin [aut, cre], Yuanhua Huang [aut], Davis McCarthy [aut]

Maintainer: Jeffrey Pullin <jpullin at>

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biocViews ExomeSeq, GeneExpression, RNASeq, Sequencing, SingleCell, Software, Transcriptomics, Visualization
Version 1.0.0
In Bioconductor since BioC 3.16 (R-4.2) (< 6 months)
License GPL-3
Depends R (>= 4.2), stats
Imports combinat, GenomeInfoDb, GenomicRanges, ggplot2, ggtree, Matrix, matrixStats, methods, pheatmap, snpStats, S4Vectors, utils, VariantAnnotation, vcfR
Suggests BiocStyle, foreach, knitr, pcaMethods, rmarkdown, testthat, VGAM
Enhances doMC
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