logVarGenes: Find highly variable genes (log linear model)

Description Usage Arguments Details Value Author(s)

Description

Find highly variable genes (log linear model)

Usage

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logVarGenes(scd, minMean = 0, fraction = 0.05, lower = FALSE,
  residualsInLogSpace = TRUE, quadratic = TRUE, se = qnorm(p = 0.975))

Arguments

scd

Single Cell Dataset

minMean

Fit model to genes with mean expression gretaer than minMean

fraction

The fraction of cells on

lower

By default this function will only winsorise the upper end. If you also require the bottom end to be winsorised set this to TRUE.

residualsInLogSpace

Use lm instead of nls to optimise residuals in log-space.

quadratic

Fit an order 2 model to log cv-squared against log mean

se

The number of standard errors to return.

Details

Find highly variable genes (log linear model). Model is fitted to:

\frac{σ^{2}}{μ^{2}} = a * μ^{k}

Using the non-linear squares method, if residualsInLogSpace is FALSE. Otherwise using a linear model +/- a quadartic term.

Value

Returns a list of means, cv2, fit object and variable genes

Author(s)

Wajid Jawaid


wjawaid/bglab documentation built on May 4, 2019, 6:33 a.m.