fit_de_model: Differential feature analysis

In zentnerlab/TSRexploreR: TSS and TSR Analysis

Differential feature analysis

Description

Find differential TSSs or TSRs.

Usage

fit_de_model(
  experiment,
  formula,
  data_type = c("tss", "tsr"),
  samples = "all",
  method = "DESeq2"
)

Arguments

experiment	TSRexploreR object.
formula	Formula for differenatial feature analysis.
data_type	Whether TSSs ('tss') or TSRs ('tsr') should be analyzed
samples	A vector of sample names to analyze.
method	Build DE model using either 'DESeq2' or 'edgeR'.

Details

This function uses either DESeq2 or edgeR to find differential TSSs or TSRs. 'formula' should be a valid R formula in any form accepted by DESeq2 or edgeR, where the formula components are any columns present in the sample sheet.

Value

TSRexploreR object with stored DE model.

See Also

differential_expression to extract differential TSSs or TSRs from model.

Examples

data(TSSs)
sample_sheet <- data.frame(
  sample_name=c(
    sprintf("S288C_D_%s", seq_len(3)),
    sprintf("S288C_WT_%s", seq_len(3))
  ),
  file_1=rep(NA, 6), file_2=rep(NA, 6),
  condition=c(
    rep("Diamide", 3),
    rep("Untreated", 3)
  )
)

exp <- TSSs %>%
  tsr_explorer(sample_sheet=sample_sheet) %>%
  format_counts(data_type="tss")

exp <- fit_de_model(exp, data_type="tss", formula=~condition, method="edgeR")

zentnerlab/TSRexploreR documentation built on Dec. 30, 2022, 10:27 p.m.