This is the development version of barbieQ; for the stable release version, see barbieQ.
Analyze Barcode Data from Clonal Tracking ExperimentsBioconductor version: Development (3.22)
The barbieQ package provides a series of robust statistical tools for analysing barcode count data generated from cell clonal tracking (i.e., lineage tracing) experiments. In these experiments, an initial cell and its offspring collectively form a clone (i.e., lineage). A unique barcode sequence, incorporated into the DNA of the inital cell, is inherited within the clone. This one-to-one mapping of barcodes to clones enables clonal tracking of their behaviors. By counting barcodes, researchers can quantify the population abundance of individual clones under specific experimental perturbations. barbieQ supports barcode count data preprocessing, statistical testing, and visualization.
Author: Liyang Fei [aut, cre] ORCID: 0000-0002-3293-2094
Maintainer: Liyang Fei <liyang.fei at petermac.org>
Citation (from within R, entercitation("barbieQ")
): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("barbieQ")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("barbieQ")
Details biocViews Preprocessing, Regression, Sequencing, Software, Visualization Version 1.1.2 In Bioconductor since BioC 3.21 (R-4.5) (< 6 months) License GPL-3 Depends R (>= 4.5) Imports magrittr, tidyr, dplyr, grid, circlize, ComplexHeatmap, ggplot2, logistf, limma, stats, igraph, utils, data.table, S4Vectors, SummarizedExperiment System Requirements URL https://github.com/Oshlack/barbieQ/issues Bug Reports https://github.com/Oshlack/barbieQ See More Package Archives
Follow Installation instructions to use this package in your R session.
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