estimateFreqVar: Estimate the mean and variation in each cell state's...
In immunogenomics/scpost: Simulates single-cell datasets from input data

Given a metadata table containing each cell's sample identity and assigned cell state, this function will return a list containing: a vector containing the mean frequency of each cell state (in linear space) and a variance-covariance matrix containing the covariances between each cell state (log space by default). Both of these elements are used as direct inputs to our dataset generation functions.

1	estimateFreqVar(meta, clusCol, sampleCol, logCov = TRUE)

`meta`	A metadata table that should include named columns containing: Cell IDs, cell state assignments, and sample identities for each cell.
`clusCol`	The name of the metadata column containing the cell state cluster assignments for each cell.
`sampleCol`	The name of the metadata column containing the sample identities of each cell.
`logCov`	Boolean designating whether you want the variance-covariance matrix in log space (default) or in linear space. The log space matrix is used as input to our simulation functions; only use linear space for visualization.

Returns a list containing: a vector containing the mean frequency of each cell state (in linear space) and a variance-covariance matrix containing the covariances between each cell state (log space by default). The mean frequency vector will be transformed into log space during data simulation.

immunogenomics/scpost documentation built on July 28, 2021, 4:03 a.m.