qscores {MANOR} | R Documentation

## Examples of qscore objects (quality scores) to apply to CGH arrays

### Description

This data set provides `qscore` objects that can be applied to normalized `arrayCGH` objects in order to evaluate data quality after normalization.

### Usage

    data(qscores)

### Format

The following `qscore` objects are provided:

| `clone.qscore` | number of clones
| `pct.clone.qscore` | percentage of clones
| `pct.spot.qscore` | percentage of spots
| `pct.spot.before.qscore` | percentage of spots before normalization
| `pct.replicate.qscore` | average percentage of replicates
| `smoothness.qscore` | signal smoothness
| `var.replicate.qscore` |
| `dyn.x.qscore` | signal dynamics on X chromosome
| `dyn.y.qscore` | signal dynamics on Y chromosome

### Note

People interested in tools for array-CGH analysis can visit our web-page: http://bioinfo.curie.fr.

### Author(s)

Pierre Neuvial, manor@curie.fr.

### Source

Institut Curie, manor@curie.fr.

### See Also

`spatial`, `qscore.summary.arrayCGH`, `qscore`

### Examples

    data(qscores)
    data(spatial)

    ## define a list of qscores
    qscore.list <- list(clone=clone.qscore, pct.clone=pct.clone.qscore,
    pct.spot=pct.spot.qscore, pct.replicate=pct.replicate.qscore,
    smoothness=smoothness.qscore, dyn.x=dyn.x.qscore, dyn.y=dyn.y.qscore,
    var.replicate=var.replicate.qscore)

    ## compute quality scores for a couple of normalized arrays
    gradient.norm$quality <- qscore.summary.arrayCGH(gradient.norm,
    qscore.list)
    print(gradient.norm$quality[, 2:3])

    qscore.list$dyn.x$args$test <- 23
    qscore.list$dyn.y$args$test <- 24
    edge.norm$quality <- qscore.summary.arrayCGH(edge.norm, qscore.list)
    print(edge.norm$quality[, 2:3])

[Package MANOR version 1.16.0 Index]