limma_treat_find_all_markers: Find markers for each group by limma's pairwise moderated...

In jdreyf/jdcbioinfo: Joslin Diabetes Center bioinformatics utilities

Find markers for each group by limma's pairwise moderated t-tests over a logFC cutoff

Description

Perform limma's pairwise moderated t-tests, find specifically up or down-regulated markers for each group over a logFC cutoff.

Usage

limma_treat_find_all_markers(
  object,
  grp,
  direction = c("up", "down"),
  treat.lfc = log2(1.2),
  design = NULL,
  add.means = !is.null(grp),
  adjust.method = "BH",
  weights = NA,
  trend = FALSE,
  block = NULL,
  correlation = NULL,
  moderated = TRUE
)

Arguments

object	Matrix-like data object containing log-ratios or log-expression values, with rows corresponding to features (e.g. genes) and columns to samples. Must have row names that are non-duplicated and non-empty.
grp	Vector of sample groups. These must be valid variable names in R and the same length as ncol(object).
direction	Either "up" or "down" or both
treat.lfc	Vector of logFC passed to treat lfc. It is recycled as needed to match rows of object. If given, length(contrast.v) must be 1. McCarthy & Smyth suggest a 10 which is treat.lfc=log2(1.1).
design	Design matrix of the experiment, with rows corresponding to samples and columns to coefficients to be estimated.
add.means	Logical indicating if (unweighted) group means per row should be added to the output.
adjust.method	Method used to adjust the p-values for multiple testing. Options, in increasing conservatism, include "none", "BH", "BY", and "holm". See p.adjust for the complete list of options. A NULL value will result in the default adjustment method, which is "BH".
weights	Non-negative observation weights. Can be a numeric matrix of individual weights of same size as the object, or a numeric vector of sample weights with length ncol(object), or a numeric vector of gene weights with length equal to nrow(object). Set to NULL to ignore object$weights. weights=NA (with length one) doesn't pass weights to limma.
trend	Logical; should an intensity-trend be allowed for the prior variance? Default is that the prior variance is constant.
block	Vector specifying a blocking variable on the samples. Has length = ncol(object). Must be NULL if ndups > 1.
correlation	Inter-duplicate or inter-technical replicate correlation. Must be given if ndups>1 or !is.null(block).
moderated	Logical; should eBayes be used? Otherwise an unmoderated version for limma to produce ordinary least squares statistics is used.

Value

Data frame.

jdreyf/jdcbioinfo documentation built on Feb. 12, 2025, 4:30 p.m.