signeR {signeR} | R Documentation

## signeR

### Description

Generates the signatures.

### Usage

        signeR(M, Mheader = TRUE, samples = "rows", Opport = NA,
            Oppheader = FALSE, nsig = NA, nlim = c(NA, NA),
            try_all = FALSE, ap = NA, bp = NA, ae = NA, be = NA,
            lp = NA, le = NA, var.ap = 10, var.ae = 10,
            testing_burn = 1000, testing_eval = 1000, EM_eval = 100,
            main_burn = 10000, main_eval = 2000, start = "lee",
            estimate_hyper = FALSE, EMit_lim=100)

### Arguments

`M` | mutation counts matrix of samples x features.
`Mheader` | if M have colnames defined use TRUE, if FALSE a default order will be assumed.
`samples` | if the samples are row-wise or column-wise in M, default is "row".
`Opport` | context count matrix of samples x features in the target genome or region.
`Oppheader` | if Opport have header defined.
`nsig` | number of signatures, which can be provided or estimated by the algorithm.
`nlim` | define a interval to search for the optimal number of signatures.
`try_all` | if true, all possible values for nsig will be tested
`ap` | shape parameter of the gamma distribution used to generate the entries of a matrix of rate parameters of the gamma distributions which generate signatures.
`bp` | rate parameter of the gamma distribution used to generate the entries of a matrix of rate parameters of the gamma distributions which generate signatures.
`ae` | shape parameter of the gamma distribution used to generate the entries of a matrix of rate parameters of the gamma distributions which generate exposures.
`be` | rate parameter of the gamma distribution used to generate the entries of a matrix of rate parameters of the gamma distributions which generate exposures.
`lp` | parameter of the exponential distribution used to generate the entries of a matrix of shape parameters of the gamma distributions which generate signatures.
`le` | parameter of the exponential distribution used to generate the entries of a matrix of shape parameters of the gamma distributions which generate exposures.
`var.ap` | variance of the gamma distribution used to generate proposals for shape parameters of signatures
`var.ae` | variance of the gamma distribution used to generate proposals for shape parameters of exposures
`testing_burn` | number of burning iterations of the Gibbs sampler used to estimate the number of signatures in data. Corresponds to R0 at Algorithm 1 on signeR paper.
`testing_eval` | number of iterations of the Gibbs sampler used to estimate the number of signatures in data. Corresponds to R2 at Algorithm 1 on signeR paper.
`EM_eval` | number of samples generated at each iteration of the EM algorithm. Corresponds to R1 at Algorithm 1 on signeR paper.
`main_burn` | number of burning iterations of the final Gibbs sampler.
`main_eval` | number of iterations of the final Gibbs sampler.
`start` | NMF algorithm used to generate initial values for signatures and exposures,options: "brunet","KL","lee","Frobenius","offset","nsNMF", "ls-nmf","pe-nmf","siNMF","snmf/r" or "snmf/l".
`estimate_hyper` | if TRUE, algorithm estimates optimal values of ap,bp,ae,be,lp,le. Start values can still be provided.
`EMit_lim` | limit of EM iterations for the estimation of hyper-hyperparameters ap,bp,ae,be,lp,le. Default is 100. Corresponds to U at Algorithm 1 on signeR paper.

### Value

signeR output is a list with the following items:

`Nsign` | selected number of signatures.
`tested_n` | array containing the numbers of signatures tested by the algorithm.
`Test_BICs` | list of measured BIC values when testing different numbers of signatures.
`Phat` | Estimated signatures, median of P samples.
`Ehat` | Estimated exposures, median of E samples.
`SignExposures` | SignExp object which contain the set of samples for the model parameters.
`Bics` | measured BIC values on the final run of the sampler.
`HyperParam` | evolution of estimated hyperparameters when testing different numbers of signatures.

### Examples

    vignette(package="signeR")

[Package signeR version 1.6.1 Index]