displaySummaryBASiCS-BASiCS_Summary-method

displaySummaryBASiCS

displaySummaryBASiCS,BASiCS_Summary-method

an object of class <code><a href="/link/?package=BASiCS&version=1.1.0" basics_summary'="" data-mini-rdoc="BASiCS::"></a>'>BASiCS_Summary</code>

object

Name of the slot to be used for the accessed. 
Possible values: <code>'mu'</code>, <code>'delta'</code>, <code>'phi'</code>, 
<code>'s'</code>, <code>'nu'</code> and <code>'theta'</code>

Param

Accessors for the slots of a <code><a href="/link/?package=BASiCS&version=1.1.0" basics_summary'="" data-mini-rdoc="BASiCS::"></a>'>BASiCS_Summary</code>
object

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

displaySummaryBASiCS-BASiCS_Summary-method function

an object of class <code><a href='<a href='BASiCS_Summary'></a>'>BASiCS_Summary</a></code>

Accessors for the slots of a <code><a href='<a href='BASiCS_Summary'></a>'>BASiCS_Summary</a></code>
object

Accessors for the slots of a <code><a href='<a href='BASiCS_Summary'></a>'>BASiCS_Summary</a></code> object — displaySummaryBASiCS-BASiCS_Summary-method

Accessors for the slots of a <code><a href='<a href='BASiCS_Summary'></a>'>BASiCS_Summary</a></code> object

Accessors for the slots of a <code><a href="/link/?package=BASiCS&version=1.1.0" basics_summary'="" data-mini-rdoc="BASiCS::"></a>'>BASiCS_Summary</code> object

displaySummaryBASiCS-BASiCS_Summary-method: Accessors for the slots of a `'>BASiCS_Summary` object

Description

Usage

Arguments

Value

References

See Also

Examples