Model selection and robust inference of mutational signatures using ...

The spectrum of mutations in a collection of cancer genomes can be described by a mixture of a few mutational signatures.

We propose a Negative Binomial NMF with a patient specific dispersion parameter to capture the variation across patients and derive the corresponding update ...

Model selection and robust inference of mutational signatures using ...

Title:Model selection and robust inference of mutational signatures using Negative Binomial non-negative matrix factorization ... Abstract:The ...

[PDF] Model selection and robust inference of mutational signatures ...

A novel model selection procedure inspired by cross-validation to determine the number of signatures with a Negative Binomial NMF with a patient specific ...

Model selection and robust inference of mutational signatures using ...

We also show that our model selection procedure is more accurate than the available methods in the literature for finding the true number of signatures. Lastly, ...

(PDF) Model selection and robust inference of mutational signatures ...

PDF | Background The spectrum of mutations in a collection of cancer genomes can be described by a mixture of a few mutational signatures. The.

Model selection and robust inference of mutational signatures using ...

Model selection and robust inference of mutational signatures using Negative Binomial non-negative matrix factorization. Marta Pelizzola 1. ,. Ragnhild Laursen ...

Model selection and robust inference of mutational signatures using ...

Abstract Background The spectrum of mutations in a collection of cancer genomes can be described by a mixture of a few mutational signatures.

Peer Review reports - BMC Bioinformatics

Model selection and robust inference of mutational signatures using Negative Binomial non-negative matrix factorization

Robust discovery of mutational signatures using power posteriors

We propose a new approach to mutational signatures analysis that improves robustness to misspecification by using a power posterior for a fully ...

Robust discovery of mutational signatures using power posteriors

Reproducible model selection using bagged posteriors. Bayesian Analysis, 18(1):79, 2023. J. H. Huggins and J. W. Miller. Reproducible ...

MartaPelizzola/SigMoS: Cross-validation and model ... - GitHub

For more information about SigMoS see our manuscript on bioRxiv "Model selection and robust inference of mutational signatures using Negative Binomial non- ...

A comprehensive comparison of tools for fitting mutational signatures

Mutational signatures connect characteristic mutational patterns in the genome with biological or chemical processes that take place in ...

Flexible model-based non-negative matrix factorization ... - De Gruyter

Somatic mutations in cancer can be viewed as a mixture distribution of several mutational signatures, which can be inferred using non-negative ...

Uncovering novel mutational signatures by de novo extraction with ...

Ratio of approximately 1.00 indicates a similar performance between suggested and forced model selection. (D) Summary of the performance for the ...

De novo mutational signature discovery in tumor genomes using ...

The extent of regularization is controlled by a learned parameter, λ, for the entire signature matrix. We note that if the underlying signatures are very ...

MUSE-XAE: MUtational Signature Extraction with eXplainable ...

Mutational signatures are a critical component in deciphering the genetic alterations that underlie cancer development and have become a ...

Learning mutational signatures and their multidimensional genomic ...

A number of studies have analysed cancer genomes to extract such mutational signatures using computational pattern recognition algorithms such ...

Uncovering novel mutational signatures by de novo extraction with ...

selection of the number of signatures, yields robust solutions, ... model selection results in equal numbers of false-posi- tive and false ...

signeR: an empirical Bayesian approach to mutational signature ...

While requiring minimal intervention from the user, our method addresses the determination of the number of signatures directly as a model selection problem. In ...