lmFitC: Fit linear model for each gene given a series of arrays....

In BatchQC: Batch Effects Quality Control Software

Description

Fit linear model for each gene given a series of arrays. This is the standard lmFit function from limma package with the modification to accept an additional correlation matrix parameter option

Usage

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

Arguments

object	A matrix-like data object containing log-ratios or log-expression values for a series of arrays, with rows corresponding to genes and columns to samples. Any type of data object that can be processed by getEAWP is acceptable.
design	the design matrix of the microarray experiment, with rows corresponding to arrays and columns to coefficients to be estimated. Defaults to the unit vector meaning that the arrays are treated as replicates
ndups	positive integer giving the number of times each distinct probe is printed on each array.
spacing	positive integer giving the spacing between duplicate occurrences of the same probe, spacing=1 for consecutive rows.
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	the inter-duplicate or inter-technical replicate correlation
cormatrix	the complete correlation matrix of the samples
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 to be passed to lm.series, gls.series or mrlm

Value

list containing log2(quantile counts per mil reads) and library sizes

BatchQC documentation built on Nov. 8, 2020, 8:30 p.m.