EcoliOxygen {qpgraph} | R Documentation

## Preprocessed microarray oxygen deprivation data and filtered RegulonDB data

### Description

The data consist of two objects, one containing normalized gene expression microarray data from Escherichia coli (E. coli) and the other containing a subset of filtered RegulonDB transcription regulatory relationships on E. coli.

### Usage

    data(EcoliOxygen)

### Format

`gds680.eset` | `ExpressionSet` object containing n=43 experiments of various mutants under oxygen deprivation (Covert et al., 2004). The mutants were designed to monitor the response from E. coli during an oxygen shift in order to target the a priori most relevant part of the transcriptional network by using six strains with knockouts of five key transcriptional regulators in the oxygen response (arcA, appY, fnr, oxyR and soxS). The data was obtained by downloading the corresponding CEL files from the Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo) under accession `GDS680` and then normalized using the `rma()` function from the `affy` package. Following the steps described in (Castelo and Roverato, 2008) probesets were mapped to Entrez Gene Identifiers and filtered such that the current `ExpressionSet` object contains a total of p=4205 genes. The slot `featureNames` has already the corresponding Entrez Gene IDs.
`filtered.regulon6.1` | Data frame object containing a subset of the E. coli transcriptional network from RegulonDB 6.1 (Gama-Castro et al, 2008) obtained through the filtering steps described in (Castelo and Roverato, 2008). In this data frame each row corresponds to a transcriptional regulatory relationship and the first two columns contain Blattner IDs of the transcription factor and target genes, respectively, and the following two correspond to the same genes but specified by Entrez Gene IDs. The fifth column contains the direction of the regulation according to RegulonDB.

### Source

Covert, M.W., Knight, E.M., Reed, J.L., Herrgard, M.J., and Palsson, B.O. Integrating high-throughput and computational data elucidates bacterial networks. Nature, 429(6987):92-96, 2004.

Gama-Castro, S., Jimenez-Jacinto, V., Peralta-Gil, M., Santos-Zavaleta, A., Penaloza-Spinola, M.I., Contreras-Moreira, B., Segura-Salazar, J., Muniz-Rascado, L., Martinez-Flores, I., Salgado, H., Bonavides-Martinez, C., Abreu-Goodger, C., Rodriguez-Penagos, C., Miranda-Rios, J., Morett, E., Merino, E., Huerta, A.M., Trevino-Quintanilla, L., and Collado-Vides, J. RegulonDB (version 6.0): gene regulation model of Escherichia coli K-12 beyond transcription, active (experimental) annotated promoters and Textpresso navigation. Nucleic Acids Res., 36(Database issue):D120-124, 2008.

### References

Castelo, R. and Roverato, A. Reverse engineering molecular regulatory networks from microarray data with qp-graphs. J. Comp. Biol., accepted, 2008.

### Examples

    data(EcoliOxygen)

[Package qpgraph version 1.0.0 Index]