thresholdFingerprint {pathprint} | R Documentation

## Apply threshold values to produce a Pathway Fingerprint

### Description

Function to produce ternary threshold values, Pathway Fingerprint scores, from continuous geneset enrichment values. Returns ternary scores for each pathway, high (1), mid (0), low (-1)

### Usage

    thresholdFingerprint(SCE, platform)

### Arguments

`SCE` | Pathway enrichment matrix from `single.chip.enrichment`
`platform` | GEO platform ID for array used

### Details

The thresholds have been pre-calculated and optimized against a panel of tissue samples (see ref).

### Value

Matrix containing ternary scores for each sample in the SCE input matrix. Rownames are genesets and colnames are the columns of the SCE matrix.

### Author(s)

Gabriel Altshuler

### 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

`exprs2fingerprint`, `platform.thresholds`

### Examples

    require(pathprintGEOData)
    library(SummarizedExperiment)

    # load  the data
    data(SummarizedExperimentGEO)

    # Comparing workflows

    # 1. Pathway Fingerprint scores from exprs2fingerprint

    # Use ALL dataset as an example

    require(ALL)
    data(ALL)
    annotation(ALL)

    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

    # Analyze patients with ALL1/AF4 and BCR/ABL translocations
    ALL.eset <- ALL[,1:5]
    ALL.exprs<-exprs(ALL.eset)
    # Process fingerprints
    ALL.fingerprint<-exprs2fingerprint(exprs = ALL.exprs,
        platform = "GPL8300",
        species = "human",
        progressBar = TRUE
        )

    # 2. Thresholded pathway enrichment values

    # Annotate
    ALL.exprs.entrez <- customCDFAnn(ALL.exprs, chipframe$GPL8300$ann)

    # Pathway enrichment
    ALL.enrichment <- single.chip.enrichment(exprs = ALL.exprs.entrez,
        geneset = pathprint.Hs.gs,
        transformation = "squared.rank",
        statistic = "mean",
        normalizedScore = FALSE,
        progressBar = TRUE
        )

    # Threshold
    ALL.enrichment.threshold <- thresholdFingerprint(
        ALL.enrichment, "GPL8300")

    # Compare 1. and 2.
    all.equal(ALL.enrichment.threshold, ALL.fingerprint)

[Package pathprint version 1.10.4 Index]