Description Usage Arguments Value Author(s) References See Also Examples
View source: R/composeGenomesFromExposures.R
'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.
1 | composeGenomesFromExposures(exposures, signatures)
|
exposures |
(Mandatory) A single vector or list of vectors containing
the estimated signature contributions/exposures as computed by the function
|
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. |
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.
Rosario M. Piro
Politecnico di Milano
Maintainer: Rosario
M. Piro
E-Mail: <rmpiro@gmail.com> or <rosariomichael.piro@polimi.it>
http://rmpiro.net/decompTumor2Sig/
Krueger, Piro (2019) decompTumor2Sig: Identification of mutational
signatures active in individual tumors. BMC Bioinformatics
20(Suppl 4):152.
decompTumor2Sig
decomposeTumorGenomes
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ### 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)
|
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