foldFiltBM: Output Fold Change Data using biomaRt

Description

This function is designed to take an ExpressionSet and some comparisons and output HTML tables. It is very similar to foldFilt except it uses the biomaRt package to annotate genes and the annotate package to create the HTML table(s).

Usage

foldFiltBM(object, fold = 1, groups, comps, compnames, species, links = linksBM()[1:3], otherann = annBM()[1:3], filterfun = NULL, ann.source = "entrezgene", affyid = FALSE, html = TRUE, text = TRUE, save = FALSE)

Arguments

object

An ExpressionSet object

fold

The log fold change cutoff to use. Note that this is log base two.

groups

A vector of group identifiers. Probably easiest to use a numeric vector

comps

A list containing all the comparisons to be made. Each list item should be a vector of length two. See details for more information.

compnames

A character vector of the names for each of the comparisons to be made. This will be the name of the resulting HTML or text file.

species

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

links

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

otherann

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

filterfun

A filtering function created by genefilter to filter the data using additional criteria. See details for more information

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.

affyid

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

html

Boolean. Output HTML tables? Defaults to TRUE

text

Boolean. Output text tables? Defaults to TRUE

save

Boolean. If TRUE, a list will be returned. The first item in the list will be a vector showing the number of 'significant' genes for each comparison. The second item will be a matrix of -1's, 0's and 1's indicating a significant difference, and the direction of the difference. The first item is useful for creating Sweave - based reports and the second is useful for making Vennn diagrams using vennDiagram from the limma package.

Value

Returns a list; see above for the elements of the list. This function is mainly called for the side effect of outputting HTML or text files containing annotated 'significant' gene lists.

Details

This function is useful for outputting annotated gene lists for multiple fold change comparisons. The genes will be ordered by the absolute fold change.

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 getAffyArrays.

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]].

One can also protect against selecting probesets that have very small expression values for all samples (which likely have a large fold change due to noise, rather than signal) by using the filterfun argument. An example would be:

f <- kOverA(1, 6)

filt <- filterfun(f)

Then add filterfun = filt as an argument to the call to foldFilt.