evaluateDecompositionQuality {decompTumor2Sig} | R Documentation

## Evaluate tumor decomposition quality.

### Description

'evaluateDecompositionQuality()' evaluates the quality of the decomposition into exposures of a single tumor. The function evaluates the quality of a decomposition obtained from the function `decomposeTumorGenomes` by comparing the re-composed (=re-constructed) tumor genome mutation frequencies to those actually observed in the tumor genome. Tumor genome mutation frequencies are reconstructed using `composeGenomesFromExposures` and the results can optionally be plotted.

### Usage

    evaluateDecompositionQuality(exposure, signatures, genome,
    plot=FALSE)

### Arguments

`exposure` | (Mandatory) A single vector containing the estimated signature contributions, or exposures, of a single tumor as provided by `decomposeTumorGenomes`. The number of elements of the exposure vector must correspond to the number of signatures (see below).
`signatures` | (Mandatory) The list of signatures (vectors, data frames or matrices) for which the exposures were obtained. Each of the list objects represents one mutational signature. Vectors are used for Alexandrov signatures, data frames or matrices for Shiraishi signatures.
`genome` | (Mandatory) A single tumor genome in form of mutation frequencies specified either in the Alexandrov or the Shiraishi format (must match the format used for `signatures`, see above).
`plot` | (Optional) If `FALSE` (default), the numerical results (see below) will be returned. If `TRUE`, the reconstructed mutation frequencies will be plotted against the original, observed mutation frequencies and the numerical results will be integrated as text labels in the plot.

### Value

A named list object containing measurements for the Pearson correlation coefficient between the reconstructed and observed mutation frequencies, and the explained variance; or alternatively, a plot with these measurements (see option `plot` above).

### Author(s)

Rosario M. Piro
Freie Universitaet Berlin
Maintainer: Rosario M. Piro
E-Mail: <rmpiro@gmail.com> or <r.piro@fu-berlin.de>

Rosario M. Piro, Freie Universitaet Berlin, rmpiro@gmail.com

### References

http://rmpiro.net/decompTumor2Sig/
Krueger, Piro (2018) decompTumor2Sig: Identification of mutational signatures active in individual tumors. BMC Bioinformatics (accepted for publication).
Krueger, Piro (2017) Identification of Mutational Signatures Active in Individual Tumors. NETTAB 2017 - Methods, Tools & Platforms for Personalized Medicine in the Big Data Era, October 16-18, 2017, Palermo, Italy. PeerJ Preprints 5:e3257v1, 2017.

### See Also

`decompTumor2Sig`
`decomposeTumorGenomes`
`composeGenomesFromExposures`
`computeExplainedVariance`

### Examples

    ### get Alexandrov signatures from COSMIC
    signatures <- readAlexandrovSignatures()

    ### load preprocessed breast cancer genomes (object 'genomes') from
    ### Nik-Zainal et al (PMID: 22608084)
    gfile <- system.file("extdata",
             "Nik-Zainal_PMID_22608084-genomes-Alexandrov_3bases.Rdata",
             package="decompTumor2Sig")
    load(gfile)

    ### compute exposures
    exposures <- decomposeTumorGenomes(genomes, signatures, verbose=FALSE)

    ### evaluate the decomposition by comparing to the original data
    evaluateDecompositionQuality(exposures[[1]], signatures, genomes[[1]])

[Package decompTumor2Sig version 2.0.0 Index]