BASiCS_D_TestDE

<p>This function is no longer in use and will 
be removed from future releases of <code>BASiCS</code>. 
Please use <code><a rd-options="BASiCS" href="/link/BASiCS_TestDE?package=BASiCS&version=1.1.0&to=BASiCS" data-mini-rdoc="BASiCS::BASiCS_TestDE">BASiCS_TestDE</a></code> instead.</p>

Single-cell mRNA sequencing can uncover novel cell-to-cell
heterogeneity in gene expression levels in seemingly homogeneous populations
of cells. However, these experiments are prone to high levels of technical noise,
creating new challenges for identifying genes that show genuine heterogeneous
expression within the population of cells under study. BASiCS (Bayesian Analysis
of Single-Cell Sequencing data) is an integrated Bayesian hierarchical model to
perform statistical analyses of single-cell RNA sequencing datasets in the context
of supervised experiments (where the groups of cells of interest are known a priori,
e.g. experimental conditions or cell types). BASiCS performs built-in data normalisation
(global scaling) and technical noise quantification (based on spike-in genes).
BASiCS provides an intuitive detection criterion for highly (or lowly)
variable genes within a single group of cells. Additionally, BASiCS can
compare gene expression patterns between two or more pre-specified groups of cells.
Unlike traditional differential expression tools, BASiCS quantifies changes
in expression that lie beyond comparisons of means, also allowing the study
of changes in cell-to-cell heterogeneity. The latter are quantified via a
biological over-dispersion parameter that measures residual over-dispersion
(with respect to Poisson sampling) after normalisation and technical noise removal.

Catalina Vallejos

BASiCS

Bayesian Analysis of Single-Cell Sequencing data

Nils Eling

Sylvia Richardson

John Marioni

BASiCS_D_TestDE function

<p>This function is no longer in use and will 
be removed from future releases of <code>BASiCS</code>. 
Please use <code><a rd-options='BASiCS' href='BASiCS_TestDE'>BASiCS_TestDE</a></code> instead.</p>

BASiCS_D_TestDE: Detection of genes with changes in expression.

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Examples