Palash Pandey1,2, Sanjeevani Arora1,3, Gail L Rosen2. 1. Cancer Prevention and Control Program, Fox Chase Cancer Center, Philadelphia, PA, USA. 2. Ecological and Evolutionary Signal-processing and Informatics Laboratory, Department of Electrical and Computer Engineering, College of Engineering, Drexel University, Philadelphia, PA, USA. 3. Department of Radiation Oncology, Fox Chase Cancer Center, Philadelphia, PA, USA.
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 nontrivial 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: MetaMutationalSigs is implemented using R and python and is available for installation using Docker and available at: https://github.com/EESI/MetaMutationalSigs. SUPPLEMENTARY INFORMATION: More information about the package including test data and results are available at https://github.com/EESI/MetaMutationalSigs.
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 nontrivial 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: MetaMutationalSigs is implemented using R and python and is available for installation using Docker and available at: https://github.com/EESI/MetaMutationalSigs. SUPPLEMENTARY INFORMATION: More information about the package including test data and results are available at https://github.com/EESI/MetaMutationalSigs.
Authors: John N Weinstein; Eric A Collisson; Gordon B Mills; Kenna R Mills Shaw; Brad A Ozenberger; Kyle Ellrott; Ilya Shmulevich; Chris Sander; Joshua M Stuart Journal: Nat Genet Date: 2013-10 Impact factor: 38.330
Authors: Kenichi Yoshida; Kate H C Gowers; Henry Lee-Six; Deepak P Chandrasekharan; Tim Coorens; Elizabeth F Maughan; Kathryn Beal; Andrew Menzies; Fraser R Millar; Elizabeth Anderson; Sarah E Clarke; Adam Pennycuick; Ricky M Thakrar; Colin R Butler; Nobuyuki Kakiuchi; Tomonori Hirano; Robert E Hynds; Michael R Stratton; Iñigo Martincorena; Sam M Janes; Peter J Campbell Journal: Nature Date: 2020-01-29 Impact factor: 49.962
Authors: Ludmil B Alexandrov; Jaegil Kim; Gad Getz; Steven G Rozen; Michael R Stratton; Nicholas J Haradhvala; Mi Ni Huang; Alvin Wei Tian Ng; Yang Wu; Arnoud Boot; Kyle R Covington; Dmitry A Gordenin; Erik N Bergstrom; S M Ashiqul Islam; Nuria Lopez-Bigas; Leszek J Klimczak; John R McPherson; Sandro Morganella; Radhakrishnan Sabarinathan; David A Wheeler; Ville Mustonen Journal: Nature Date: 2020-02-05 Impact factor: 49.962
Authors: Simon F Brunner; Nicola D Roberts; Luke A Wylie; Luiza Moore; Sarah J Aitken; Susan E Davies; Mathijs A Sanders; Pete Ellis; Chris Alder; Yvette Hooks; Federico Abascal; Michael R Stratton; Inigo Martincorena; Matthew Hoare; Peter J Campbell Journal: Nature Date: 2019-10-23 Impact factor: 49.962
Authors: Andrea Degasperi; Tauanne Dias Amarante; Jan Czarnecki; Scott Shooter; Xueqing Zou; Dominik Glodzik; Sandro Morganella; Arjun S Nanda; Cherif Badja; Gene Koh; Sophie E Momen; Ilias Georgakopoulos-Soares; João M L Dias; Jamie Young; Yasin Memari; Helen Davies; Serena Nik-Zainal Journal: Nat Cancer Date: 2020-02-17