affycoretools (version 1.38.0)

limma2biomaRt: Function to Create HTML Tables from limma Objects using biomaRt for Annotation

Description

This function is designed to take an ExpressionSet and an lmFit, model.matrix, and contrast object from limma and convert into HTML and text tables using biomaRt. The alternate function limma2biomaRt.na is designed to be run without user intervention.

Usage

limma2biomaRt(eset, fit, design, contrast, species, links = linksBM()[1:3], otherdata = annBM()[1:3], ann.source = "entrezgene", adjust = "fdr", number = 30, pfilt = NULL, fldfilt = NULL, tstat = TRUE, pval = TRUE, FC = TRUE, expression = TRUE, html = TRUE, text = TRUE, save = FALSE, addname = NULL, interactive = TRUE, affyid = FALSE)

Arguments

eset

An ExpressionSet containing affymetrix expression values.

fit

An lmFit object.

design

A model.matrix object.

contrast

A contrasts matrix from limma.

species

The species name. This must be in a particular format for biomaRt. An example for human is "hsapiens", or for mouse "mmusculus".

links

A character vector of things to annotate with hyperlinks to online databases. See linksBM for possible values.

otherdata

A character vector of things to annotate with text only (i.e., no hyperlinks). See annBM for possible values.

ann.source

The annotation source of the IDs that will be used to annotate the genes. The default value is "entrezgene". See details for other possibilities.

adjust

Multiplicity adjustment. Choices are "fdr","holm","hommel","bonferroni", or "none". Partial matching allowed.

number

Number of genes to output to table. See details for more information.

pfilt

A p-value to filter output. See details for more information.

fldfilt

A fold change to filter output. See details for more information.

tstat

Boolean: Output t-statistics in table? Defaults to FALSE.

pval

Boolean: Output (adjusted) p-values in table? Defaults to FALSE.

FC

Boolean: Output fold changes in table? Defaults to FALSE.

expression

Boolean: Output expression values in table? Defaults to TRUE.

html

Boolean: Output data in HTML tables? Defaults to TRUE.

text

Boolean: Output data in text tables? Defaults to TRUE

save

Boolean: Save tables as R objects for further processing? Defaults to FALSE.

addname

A character vector to add to the end of the automatically generated output file names. Useful for multiple calls to eliminate over-writing of existing HTML or text tables.

interactive

Boolean: Is this an interactive call, or run as part of a script (e.g., in an Sweave document)? Defaults to TRUE

affyid

Boolean. Are the IDs used to annotate these data Affymetrix IDs?

Value

If save is TRUE, a list of tables from topTable will be output.

Details

This function is designed to automatically output HTML tables, with filenames taken from the column names of the contrast matrix. The number of genes output can be controlled several different ways. First, if pfilt and fldfilt are both NULL, the top genes will be output based on the number variable. Otherwise, the genes are filtered based on p-value, fold change, or both. If the genes are filtered this way, the number of genes to be output will be listed and the filter(s) can then be adjusted if necessary.

This function currently only supports Affymetrix data. It is designed for Affymetrix chips that don't have an annotation package, which includes data that have been analyzed using the 're-mapped' CDFs supplied to BioC by MBNI at University of Michigan.

The IDs that will be used to annotate the genes depend on the source of the data. If, for example, one is using an Affymetrix chip that doesn't have a BioC annotation package, then the IDs will be Affymetrix IDs. To find out the correct name to use for the ann.source argument, one can create a connection to a Biomart database using useMart and then get a list of available Affy arrays using listFilters.

If one is using one of the re-mapped CDFs from MBNI at University of Michigan, then the IDs to use depend on the mapping used to create the CDF. At this time, only three types of CDFs can be used; EntrezGene, UniGene, and RefSeq. One can determine the correct ann.source argument by creating a connection to a Biomart database, and then calling linksBM(mart, linksBM())[[3]].

See Also

topTable, aafTableAnn