composeGenomesFromExposures {decompTumor2Sig} | R Documentation

## Compose tumor genomes from exposures.

### Description

'composeGenomesFromExposures()' re-composes (or predicts) tumor genomes (i.e., their mutation frequencies) from the given mutational signatures and their corresponding exposures, or contributions. The (re-)composition is performed by computing the weighted sum of the mutational signatures, where the weights are the exposures (=contributions) of the corresponding signatures. This can, for example, be used to verify that a decomposition obtained from `decomposeTumorGenomes` is meaningful.

### Usage

    composeGenomesFromExposures(exposures, signatures)

### Arguments

`exposures` | (Mandatory) A single vector or list of vectors containing the estimated signature contributions/exposures as computed by the function `decomposeTumorGenomes`. A list of vectors is used if the (re-)composition shall be performed for multiple genomes. The number of elements of each exposure vector must correspond to the number of `signatures`.
`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.

### Value

A list of "predicted" genomes, i.e., the frequencies of their mutational patterns computed as weighted sums of the mutational signatures, where the weights correspond to the contributions of, i.e., exposures to, the corresponding signatures.

### 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`

### 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)

    ### re-compose (predict) tumor genome features from exposures
    predGenomes <- composeGenomesFromExposures(exposures, signatures)

[Package decompTumor2Sig version 2.0.0 Index]