pluripotents.frame {pathprint} | R Documentation

## Manually curated list of pluripotent arrays

### Description

A manually compiled list of pluripotent arrays (induced pluripotent cells and embryonic stem cells) together with their GEO IDs and descriptions

### Usage

    pluripotents.frame

### Format

A data frame with 278 observations on the following 5 variables.

`GSM`

  GEO sample ID

`GSE`

  GEO series ID

`GPL`

  GEO platform ID

`source`

  GEO description - Source

`Characteristics`

  GEO description - Characteristic

### Source

http://www.ncbi.nlm.nih.gov/geo/

### 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

`consensusDistance`, `consensusFingerprint`

### Examples

    require(pathprintGEOData)
    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])

    # Extract common GSMs since we only loaded part of the geo_sum_data object
    common_GSMs <- intersect(pluripotents.frame$GSM,colnames(GEO.fingerprint.matrix))

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

    head(pluripotents.frame)

    # Use pathway fingerprints to search for
    # additional pluripotent arrays across GEO
    # create consensus pluripotent fingerprint
    pluripotent.consensus<-consensusFingerprint(
        GEO.fingerprint.matrix[,common_GSMs], threshold=0.9)

    # calculate distance from the pluripotent consensus
    geo.pluripotentDistance<-consensusDistance(
        pluripotent.consensus, GEO.fingerprint.matrix)

    # plot histograms
    par(mfcol = c(2,1), mar = c(0, 4, 4, 2))
    geo.pluripotentDistance.hist<-hist(geo.pluripotentDistance[,"distance"],
        nclass = 50, xlim = c(0,1), main = "Distance from pluripotent consensus")
    par(mar = c(7, 4, 4, 2))
    hist(geo.pluripotentDistance[pluripotents.frame$GSM, "distance"],
            breaks = geo.pluripotentDistance.hist$breaks, xlim = c(0,1),
        main = "", xlab = "above: all GEO, below: pluripotent samples")

[Package pathprint version 1.10.4 Index]