gemini_calculate_lfc: Calculate log-fold change

In gemini: GEMINI: Variational inference approach to infer genetic interactions from pairwise CRISPR screens

Description

Given a gemini.input object, calculates log-fold change from counts.

Usage

gemini_calculate_lfc(Input, counts = "counts", sample.column.name = "samplename",
normalize = TRUE, CONSTANT = 32)

Arguments

Input	a gemini.input object containing an object named counts.
counts	a character indicating the name of a matrix of counts within Input that can be used to calculate log-fold changes (defaults to "counts").
sample.column.name	a character or integer indicating which column of Input$replicate.map describes the samples.
normalize	a logical indicating if counts should be median-normalized, see Details (default = TRUE)
CONSTANT	a numeric indicating a constant value that shifts counts to reduce outliers, see Details (default = 32).

Details

See Methods from Zamanighomi et al. 2019 for a comprehensive description of the calculation of log-fold change, normalization, and count processing.

If multiple early time-points are provided for a given sample, they are treated as replicates and averaged, and used to compute log-fold change against any specified late time points.

If a sample has a specific early-time point, these are matched as long as the sample names are identical between the early and late timepoints in sample.column.name

Value

a gemini object identical to Input that also contains new objects called LFC and sample.annot.

Examples

data("Input", package = "gemini")
Input <- gemini_calculate_lfc(Input)

head(Input$LFC)

gemini documentation built on Nov. 8, 2020, 8:22 p.m.