exprs2fingerprint {pathprint} | R Documentation

## Create a pathway fingerprint from a gene expression table.

### Description

The function converts the gene expression values to a ternary matrix of pathway expression values, (-1,0,1) corresponding to (low, background, high). This is based on applying a pre-calculated threshold to pathway enrichment scores.

### Usage

    exprs2fingerprint(exprs, platform, species, progressBar = TRUE)

### Arguments

`exprs` | matrix containing a probe expression table, can be one or more columns
`platform` | microarray platform GEO ID
`species` | character string to define the species of the experiment, see details.
`progressBar` | logical. If TRUE, a progress bar is displayed while the script is running

### Details

exprs should be a matrix or dataframe of the expression values, with rownames containing probe names and colnames the experiment IDs. Platforms should be of the type listed in GEO (e.g. "GPL570"). Species can be full latin names
"Homo sapiens", "Mus musculus", "Rattus norvegicus", "Danio rerio", "Drosophila melanogaster", "Caenorhabditis elegans".
or corresponding common-use names
"human", "mouse", "rat", "zebrafish", "drosophila", "C.elegans".
The array is first annotated with Entrez Gene IDs using annotations contained in the pathprintGEOData package. Pathway expression scores are calculated by the mean-squared rank of the gene expression and normalized against the appropriate distribution for the given platform in the GEO corpus. There is a progressBar to track the script, can be set to FALSE for (possibly) marginally faster running

### Value

Returns a dataframe containing the pathway fingerprint for each of column in the expression table. Rownames correspond to pathways and colnames to the experiment IDs.

### Author(s)

Gabriel Altschuler

### References

Altschuler, G. M., O. Hofmann, I. Kalatskaya, R. Payne, S. J. Ho Sui, U. Saxena, A. V. Krivtsov, S. A. Armstrong, T. Cai, L. Stein and W. A. Hide (2013). "Pathprinting: An integrative approach to understand the functional basis of disease." Genome Med 5(7): 68.

### See Also

`consensusFingerprint`, `single.chip.enrichment`, `customCDFAnn`, `thresholdFingerprint`

### Examples

    require(pathprintGEOData)

    # Use ALL dataset as an example
    require(ALL)
    data(ALL)
    annotation(ALL)
    library(SummarizedExperiment)

    # load  the data
    data(SummarizedExperimentGEO)

    ds = c("chipframe", "genesets","pathprint.Hs.gs",
        "platform.thresholds","pluripotents.frame")
    data(list = ds)

    # extract part of the GEO.fingerprint.matrix and GEO.metadata.matrix
    GEO.fingerprint.matrix = assays(geo_sum_data[,300000:350000])$fingerprint
    GEO.metadata.matrix = colData(geo_sum_data[,300000:350000])

    # free up space by removing the geo_sum_data object
    remove(geo_sum_data)

    # The chip used was the Affymetrix Human Genome U95 Version 2 Array
    # The correspending GEO ID is GPL8300

    # Extract portion of the expression matrix and process fingerprints
    ALL.First5.fingerprint<-exprs2fingerprint(exprs = ALL[1:5],
        platform = "GPL8300",
        species = "human",
        progressBar = TRUE
    )
    head(ALL.First5.fingerprint)

[Package pathprint version 1.16.0 Index]