MetaMutationalSigs: comparison of mutational signature refitting results made easy

Author:

Pandey Palash12,Arora Sanjeevani23,Rosen Gail L1ORCID

Affiliation:

1. Ecological and Evolutionary Signal-Processing and Informatics Laboratory, Department of Electrical and Computer Engineering, College of Engineering, Drexel University, Philadelphia, PA 19104, USA

2. Cancer Prevention and Control Program, Fox Chase Cancer Center, Philadelphia, PA 19111, USA

3. Department of Radiation Oncology, Fox Chase Cancer Center, Philadelphia, PA 19111, USA

Abstract

Abstract Motivation The analysis of mutational signatures is becoming increasingly common in cancer genetics, with emerging implications in cancer evolution, classification, treatment decision and prognosis. Recently, several packages have been developed for mutational signature analysis, with each using different methodology and yielding significantly different results. Because of the non-trivial differences in tools’ refitting results, researchers may desire to survey and compare the available tools, in order to objectively evaluate the results for their specific research question, such as which mutational signatures are prevalent in different cancer types. Results Due to the need for effective comparison of refitting mutational signatures, we introduce a user-friendly software that can aggregate and visually present results from different refitting packages. Availability and implementation MetaMutationalSigs is implemented using R and python and is available for installation using Docker and available at: https://github.com/EESI/MetaMutationalSigs.

Funder

NSF

Fox Chase Cancer Center Risk Assessment Program Funds

Yale Head and Neck Cancer NIH SPORE

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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