summarise_kmFit: Summarise kmFit FDR results

In BIGslu/kimma: Kinship In Mixed Model Analysis of RNA-seq

Summarise kmFit FDR results

Description

Summarise number of significant genes at various FDR cutoffs. Can split by up/down fold change as well.

Usage

summarise_kmFit(
  fdr,
  fdr_cutoff = c(0.05, 0.1, 0.2, 0.3, 0.4, 0.5),
  p_cutoff = NULL,
  FCgroup = FALSE,
  intercept = FALSE,
  fdr.cutoff = NULL,
  p.cutoff = NULL
)

summarize_kmFit(
  fdr,
  fdr_cutoff = c(0.05, 0.1, 0.2, 0.3, 0.4, 0.5),
  p_cutoff = NULL,
  FCgroup = FALSE,
  intercept = FALSE,
  fdr.cutoff = NULL,
  p.cutoff = NULL
)

summarise_lmFit(
  fdr,
  fdr_cutoff = c(0.05, 0.1, 0.2, 0.3, 0.4, 0.5),
  p_cutoff = NULL,
  FCgroup = FALSE,
  intercept = FALSE,
  fdr.cutoff = NULL,
  p.cutoff = NULL
)

summarize_lmFit(
  fdr,
  fdr_cutoff = c(0.05, 0.1, 0.2, 0.3, 0.4, 0.5),
  p_cutoff = NULL,
  FCgroup = FALSE,
  intercept = FALSE,
  fdr.cutoff = NULL,
  p.cutoff = NULL
)

Arguments

fdr	data.frame output by kimma::kmFit( ). Main model or contrasts accepted
fdr_cutoff	numeric vector of FDR cutoffs to summarise at
p_cutoff	numeric vector of P-value cutoffs to summarise at. No FDR summary given if p.cutoff is provided
FCgroup	logical if should separate summary by up/down fold change groups
intercept	logical if should include intercept variable in summary
fdr.cutoff	Deprecated form of fdr_cutoff
p.cutoff	Deprecated form of p_cutoff

Value

Data frame with total significant genes for each variable at various FDR cutoffs

Examples

# Run kimma model
model_results <- kmFit(dat = example.voom,
      kin = example.kin,
      run_lme = TRUE, run_lmerel=TRUE, run_contrast=TRUE,
      subset_genes = c("ENSG00000250479","ENSG00000250510","ENSG00000255823"),
      model = "~ virus + asthma + (1|ptID)")

# Or extract limma results
# design <- model.matrix(~ virus + asthma, data = example.voom$targets)
# fit <- limma::eBayes(limma::lmFit(example.voom$E, design))
# model_results <- extract_lmFit(design = design, fit = fit)

# Summarise results
summarise_kmFit(fdr = model_results$lmerel, fdr_cutoff = c(0.01, 0.5),
                FCgroup = TRUE)
summarise_kmFit(fdr = model_results$lme.contrast, fdr_cutoff = c(0.01, 0.5),
                FCgroup = FALSE)

#No significant genes. No run
## summarise_kmFit(fdr = model_results$lmerel, fdr_cutoff = c(0.001))

BIGslu/kimma documentation built on May 30, 2024, 10:09 p.m.