quslmFit: LINEAR MODELS used for qusage calls the stats lm.fit call and...

In arcolombo/junk: qusage: Quantitative Set Analysis for Gene Expression

Description

LINEAR MODELS used for qusage calls the stats lm.fit call and runs a C++ code for the subsequent calculations, performance to gain with no probe weights increased. this modifies Fit genewise linear models by Gordon Smyth authored on 30 June 2003 and Last modified 6 Oct 2015. this assumes no probe weights, and least squares regression enforcing these assumptions to streamline into lm.fit and passing into C++ for moderated statistics.

Usage

quslmFit(object, design = NULL, ndups = 1, spacing = 1, block = NULL,
  correlation, weights = NULL, method = "ls", ...)

Arguments

object	expression set type
design	model.matrix built from formula
ndups	number of times each distinct probe is on array
spacing	the spacing between the next dupe, 1 for consecutive
block	vector or factor specifying a blocking variable on the arrays. Has length equal to the number of arrays. Must be ‘NULL’ if ‘ndups>2’.
correlation	inter-duplicate of inter-technical replicate correlation
weights	non-negative observation weights. Can be a numeric matrix of individual weights, of same size as the object expression matrix, or a numeric vector of array weights with length equal to ‘ncol’ of the expression matrix, or a numeric vector of gene weights with length equal to ‘nrow’ of the expression matrix.
method	fitting method; ‘"ls"’ for least squares or ‘"robust"’ for robust regression
...	other optional arguments for overloading lm.series, gls.series, or mrlm

arcolombo/junk documentation built on May 10, 2019, 12:49 p.m.