A container for storing information used in TCC

Description

This is a container class for TCC. This class initially contains count data matrix and some information for the analysis of count data. It also provides further fields that are populated during the analysis.

Details

This class is implemented as an R5 reference class. Functions calling such methods copies the object prior to calling the method to keep the semantics of functional programming. This class can be created by the generic new function with count data and associated information of experimental design.

The values (defaults to all 1) in the norm.factors field will be changed after performing the calcNormFactors function. The DEGES field stores information related to our DEGES-based normalization pipeline after performing the calcNormFactors function. The stat and estimatedDEG fields store results after performing the estimateDE function. The simulation field stores parameters used when performing the simulateReadCounts function.

Fields

This class contains the following fields:

count

numeric matrix containing count data.

gene_id

character vector indicating the identifier of the count unit, usually gene.

group

data frame indicating information about experimental design.

norm.factors

numeric vector containing normalization factors (default to 1).

stat

list for storing results after the execution of the calcNormFactors and estimateDE functions.

estimatedDEG

numeric vector as a placeholder for indicating either DEGs (flagged as "1") or non-DEGs (as "0") for individual genes. The values in this field will be populated after the execution of the estimateDE function.

simulation

list. This field is only used for analyzing simulation data.

DEGES

list for storing the information about normalization steps.

Examples

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tcc <- simulateReadCounts(Ngene = 10000, PDEG = 0.2, DEG.assign = c(0.8, 0.2),
                          DEG.foldchange = c(4, 4), replicates = c(3, 3))

# Check the TCC class object.
tcc

# Check the fields of TCC class object.
names(tcc)
head(tcc$count)

# Check the normalization factors.
tcc <- calcNormFactors(tcc, norm.method = "tmm", test.method = "edger",
                       iteration = 1, FDR = 0.1, floorPDEG = 0.05)
tcc$norm.factors

# Check the p-values and q-values.
tcc <- estimateDE(tcc, test.method = "edger", FDR = 0.1)
tcc

# Compare the breakdowns of estimated DEGs with the truth.
head(tcc$estimatedDEG)
head(tcc$simulation$trueDEG)

# M-A plotting.
plot(tcc)