## Normalisation / Agilent miRNA

### Description

Normalize Agilent miRNA arrays to remove systematic bias. Please note that if you would like to use Chipster's miRNA-specific analysis tool afterwards, you have to mark the SystematicName-column as Identifier when importing the data with the Import tool.

### Parameters

- Background treatment method (none, subtract, edwards, normexp) [normexp]
- Background offset (0, 50) [0]
- Normalize chips using the method (none, scale, quantile, vsn) [none]
- Remove control probes (no, yes) [yes]
- Chiptype (empty, Human-miRNA (v1), Human-miRNA (v2), Human-miRNA (v3), Mouse-miRNA (v1), Mouse-miRNA (v2), Rat-miRNA [empty]

### Details

There are three background removal methods: subtraction form the foreground (spot) intensities, Edward's smoothing, and normexp. For expression data the normexp method has been found to be superior to other methods, expecially when combined with background offset of 50. However, it is currently not well-understood if this is the case also for miRNA expression data.

Between array normalizations are translation to the same median, quantile, and variance stabilizing normalization. These normalizations are carried out on samples. Please note that during normalization the data is also log2-transformed.

Agilent arrays contain many control probes that might interfere with the analysis. Thus, control probes are removed at user's discretion. Please note that in order to remove the control probes, you have to mark the ControlType-column as Annotation in the Import tool.

### Output

A tab-delimited text file containing miRNA names and expression estimates. Normalization also generates a phenodata table you should fill in before any further analyses are conducted.

### References

This tool uses Bioconductor package limma.

For normalization, please cite:

Smyth, G. K., and Speed, T. P. (2003). Normalization of cDNA microarray data. Methods 31, 265-273.

For background correction steps, please cite:

Ritchie, M. E., Silver, J., Oshlack, A., Silver, J., Holmes, M., Diyagama, D., Holloway, A., and Smyth, G. K. (2007). A comparison of background correction methods for two-colour microarrays. Bioinformatics.