rsa {cellHTS2} | R Documentation

## Perform RSA ranking on the screening results.

### Description

The RSA method ranks the resulting hit list of a screening experiment, taking into account the design of the screening library (i.e., multiple probes targeting the same effector molecule).

### Usage

    rsa(x, geneColumn="GeneID", lowerBound=0, upperBound=1, reverse=FALSE, drop=FALSE)

### Arguments

`x` | Object derived from class `cellHTS`.
`geneColumn` | The name of the well annotation column to be used for the grouping of effector molecules and probes.
`lowerBound` | The lower boundary parameter for the RSA algorithm.
`upperBound` | The upper boundary parameter for the RSA algorithm.
`reverse` | Boolean. Reverse the ranking.
`drop` | Boolean. Drop all probes from the analysis for which no effector molecule is defined.

### Details

The input argument `x` has to be a `cellHTS2` object which has been scored, summarized and annotated. For details on the RSA algorithm please see the publication referenced below.

### Value

A data.frame with the following columns:

`Value of argument `geneColumn`:` | the target molecule identifier.
`Plate:` | the plate identifier.
`Well:` | the well identifier.
`Score:` | the probe score in the screen.
`RSARank:` | the computed RSA rank.
`ScoreRank:` | the rank based on a simple cutoff scheme.
`PValue:` | the computed RSA $p$-value.
`RSAHit:` | the RSA hit flag.
`#HitWell:` | the number of probes counted as positive RSA hits for a given target molecule.
`#TotalWell:` | the total number of probes for a given target molecule.
`%HitWell:` | the percentage of postive hits for a given molecule.

### Author(s)

Florian Hahne florian.hahne@novartis.com

### References

Renate Koenig, Chih-yuan Chiang, Buu P Tu, S Frank Yan, Paul D DeJesus, Angelica Romero, Tobias Bergauer, Anthony Orth, Ute Krueger, Yingyao Zhou & Sumit K Chanda: A probability-based approach for the analysis of large-scale RNAi screens

NATURE METHODS | VOL.4 NO.10 | OCTOBER 2007 | 847

### See Also

`cellHTS`

### Examples

    data(KcViabSmall)
    KcViabSmall <- scoreReplicates(KcViabSmall, sign="-", method="zscore")
    KcViabSmall <- summarizeReplicates(KcViabSmall, summary="mean")
    ranking <- rsa(KcViabSmall)
    head(ranking)

[Package cellHTS2 version 2.50.0 Index]