prepRISA: Preparation of RISA statistical data anlysis

In prepRISA: prepRISA

Description

prepRISA is a package to read RISA data coming from a sequencer and compile them into a dataframe that is suitable for multivariate data analysis.

Usage

prepRISA.CLI()
prepRISA.GUI()

Details

This function will interactively ask for a variable number of parameters. It reads a RISA file that comes from a sequencer (text file with 4 columns: 1=sample name, 2=peak number, 3=peak position (number of base pairs), 4=peak height). The data are treated according to the parameters given by the user, and a samples x peaks table is computed. This table can then be analysed with the ade4 package. Two text files are written to disk : one with all columns and one where columns of zeroes are removed.

prepRISA.CLI uses the CLI (command line interface) to dialog with the user, while prepRISA.GUI uses a Tk GUI (graphical user interface). Both interfaces call the same function prepRISAfun.

For efficiency reasons, computations are done in a C function called repClass.

Value

The prepRISA.CLI function returns invisibly the samples x peaks table as a dataframe, so that it can be used subsequently in ade4 like this:

tab <- prepRISA.CLI()
...
pca1 <- dudi.pca(tab)

Note that these tables can be quite large (hundreds of columns).

The prepRISA.GUI returns nothing, as the output dataframe is directly affected in the function:

prepRISA.GUI()
...
pca1 <- dudi.pca(tab)

Author(s)

Jean Thioulouse jean.thioulouse at univ-lyon1.fr

References

Ranjard L., Nazaret S., Gourbiere F., Thioulouse J., Linet P. & Richaume A. (2000) A soil microscale study to reveal the heterogeneity of Hg(II) impact on indigenous bacteria by quantification of adapted phenotypes and analysis of community DNA fingerprints. FEMS Microbiology Ecology, 31, 107-115.

Ranjard L., Poly F., Combrisson J., Richaume A., Gourbiere F., Thioulouse J. & Nazaret S. (2000) Heterogeneous Cell Density and Genetic Structure of Bacterial Pools Associated with Various Soil Microenvironments as Determined by Enumeration and DNA Fingerprinting Approach (RISA). Microbial Ecology, 39, 263-272.

Ranjard L., Poly F., Lata J.C., Mougel C., Thioulouse J. & Nazaret S. (2001) Characterisation of bacterial and fungal soil communities by automated-RISA (Ribosomal Intergenic Spacer Analysis) fingerprints: biological and methodological variability. Applied and Environmental Microbiology, 67, 4479-4487.

See Also

RISAtab for an example of RISA data.

Examples

## Not run: 
tab <- prepRISA()

## End(Not run)

prepRISA documentation built on May 2, 2019, 6:34 p.m.