RcadeAnalysis {Rcade} | R Documentation

## Rcade Analysis

### Description

The main function in Rcade - reads in DE information, processes ChIP data from raw .bam files, and then combines the two to form an Rcade object.

### Usage

    RcadeAnalysis(DE, ChIPannoZones, annoZoneGeneidName, ChIPtargets, ChIPfileDir, cl, DElookup, DE.prior = NULL, prior.mode="assumeIndependent", prior=NULL, ...)

### Arguments

`DE` | `Data.frame` - DE summary information for genes of interest. For example, output from limma. EITHER `DE` must have column names "geneID", "logfc" and "B" (case insensitive) OR you should specify DElookup.
`ChIPannoZones` | `GRanges` specifying the bins of interest, with a column in the metadata for the geneID.

`annoZoneGeneidName` | `character` - the name of the column in `ChIPannoZones`'s metadata corresponding to geneID.
`ChIPtargets` | `Data.frame` - Information about the ChIP data files. Mandatory column names are: "fileid", "sampleid", "factor", "filepath".
`ChIPfileDir` | `character` - Directory, within which "filepath" of `ChIPtargets` is evaluated.

`cl` | A `cluster` from `makeCluster` in the parallel package.
`DElookup` | `list` - lookup table of form `list(RcadeField1 = DEcolumn1, RcadeField2 = DEcolumn2, ...)`. If you don't specify this argument, then Rcade will try to find the mandatory fields automatically but will not keep any of the other information in its output.
`DE.prior` | `numeric` - The prior probability of DE for each GeneID. Either a scalar, or a vector where the Nth element corresponds to the Nth row of the DE argument. Ignored if `prior.mode = "assumeIndependent"`. For example, if using DE analysis from the limma package (default settings), then set `DE.prior = 0.01`.
`prior.mode` | The method used to create prior probabilities in the Rcade table. Current options are: `assumeIndependent`: Under the prior, ChIP counts and DE log ratios are assumed independent; that is, the prior is of form P(D,C)=P(D)P(C). No need to specify the `prior` argument. `keepChIP`: The prior is factorized as form P(D,C)=P(D|C)P(C). P(C) is taken from the differential count algorithm used. User must specify the `prior` argument as c(P(D|C), P(D|not C)).

`prior` | See `prior.mode`.
`...` | Additional arguments.

### Details

This is the main analysis function in Rcade. The user should specify information relating to the DE and ChIP data for the experiment in question. Rcade will process these data and rank genes by the combined DE and ChIP strength.

### Value

An Rcade object.

### Author(s)

Jonathan Cairns

### See Also

`RcadeAnalysis`

### Examples

    	dir <- file.path(system.file("extdata", package="Rcade"), "STAT1")

    	DE <- read.csv(file.path(dir, "DE.csv"))
    	DElookup <- list(GeneID="ENSG", logFC="logFC", B="B",
    "Genes.Location", "Symbol")

    	targets <- read.csv(file.path(dir, "targets.csv"), as.is = TRUE)

    	anno <- read.csv(file.path(dir, "anno.csv"))
    	anno <- anno[order(anno$chromosome_name),]
    	colnames(anno) <- c("ENSG","chr","start","end","str")
    	ChIPannoZones <- defineBins(anno, zone=c(-1500, 1500), geneID="ENSG")

    	Rcade <- RcadeAnalysis(DE, ChIPannoZones, annoZoneGeneidName="ENSG", ChIPtargets=targets, ChIPfileDir = dir,
    	DElookup=DElookup)

[Package Rcade version 1.36.0 Index]