pseudoreplicatesbynoise

"expressionmatrix" within Sincell object: numeric matrix containing a gene expression matrix gathering the expression levels of each single-cell in the experiment (displayed by columns) for each detected gene (displayed by rows)

originaldata

number of rows in list "expressionmatrix" within Sincell object

rows

number of colums in list "expressionmatrix" within Sincell object

colums

array containing the indexes indicating the limits of the deciles based on mean of gene expression

deciles

lengthdeciles

coorsorted

Vector containing for each gene in "expressionmatrix" the variance of the expression levels. Order of genes corresponds to mean expression levels (increasing order)

vargenessorted

Force the new matrix to be positive. 1 for TRUE, 0 for FALSE

positive

seed

Auxiliary function implemented in C++ making part of the sc_InSilicoCellsReplicatesObj function when its parameter method="variance.deciles".

Cell differentiation processes are achieved through a continuum of hierarchical intermediate cell-states that might be captured by single-cell RNA seq. Existing computational approaches for the assessment of cell-state hierarchies from single-cell data might be formalized under a general workflow composed of i) a metric to assess cell-to-cell similarities (combined or not with a dimensionality reduction step), and ii) a graph-building algorithm (optionally making use of a cells-clustering step). Sincell R package implements a methodological toolbox allowing flexible workflows under such framework. Furthermore, Sincell contributes new algorithms to provide cell-state hierarchies with statistical support while accounting for stochastic factors in single-cell RNA seq. Graphical representations and functional association tests are provided to interpret hierarchies. 

pseudoreplicatesbynoise: Auxiliary function of sc_InSilicoCellsReplicatesObj function used when its parameter method="variance.deciles"

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See Also