mmsig: a fitting approach to accurately identify somatic mutational signatures in hematological malignancies
Rustad et al. present a software package for the R statistical environment for the accurately quantify of somatic mutational signatures in hematological malignancies
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2021-03-01
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| Series: | Communications Biology |
| Online Access: | https://doi.org/10.1038/s42003-021-01938-0 |
| _version_ | 1818749632466911232 |
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| author | Even H. Rustad Ferran Nadeu Nicos Angelopoulos Bachisio Ziccheddu Niccolò Bolli Xose S. Puente Elias Campo Ola Landgren Francesco Maura |
| author_facet | Even H. Rustad Ferran Nadeu Nicos Angelopoulos Bachisio Ziccheddu Niccolò Bolli Xose S. Puente Elias Campo Ola Landgren Francesco Maura |
| author_sort | Even H. Rustad |
| collection | DOAJ |
| description | Rustad et al. present a software package for the R statistical environment for the accurately quantify of somatic mutational signatures in hematological malignancies |
| first_indexed | 2024-12-18T04:06:52Z |
| format | Article |
| id | doaj.art-1798eaafba7b4603af2c13853c09ffc6 |
| institution | Directory Open Access Journal |
| issn | 2399-3642 |
| language | English |
| last_indexed | 2024-12-18T04:06:52Z |
| publishDate | 2021-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Communications Biology |
| spelling | doaj.art-1798eaafba7b4603af2c13853c09ffc62022-12-21T21:21:34ZengNature PortfolioCommunications Biology2399-36422021-03-014111210.1038/s42003-021-01938-0mmsig: a fitting approach to accurately identify somatic mutational signatures in hematological malignanciesEven H. Rustad0Ferran Nadeu1Nicos Angelopoulos2Bachisio Ziccheddu3Niccolò Bolli4Xose S. Puente5Elias Campo6Ola Landgren7Francesco Maura8Myeloma Service, Department of Medicine, Memorial Sloan Kettering Cancer CenterPatologia Molecular de Neoplàsies Limfoides, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)School of Medicine, Systems Immunity Research Institute, Cardiff UniversityDepartment of Molecular Biotechnologies and Health Sciences, University of TurinDepartment of Oncology and Hemato-Oncology, University of MilanDepartamento de Bioquimica y Biologia Molecular, Instituto Universitario de Oncologia (IUOPA), Universidad de OviedoPatologia Molecular de Neoplàsies Limfoides, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)Myeloma Service, Department of Medicine, Memorial Sloan Kettering Cancer CenterMyeloma Service, Department of Medicine, Memorial Sloan Kettering Cancer CenterRustad et al. present a software package for the R statistical environment for the accurately quantify of somatic mutational signatures in hematological malignancieshttps://doi.org/10.1038/s42003-021-01938-0 |
| spellingShingle | Even H. Rustad Ferran Nadeu Nicos Angelopoulos Bachisio Ziccheddu Niccolò Bolli Xose S. Puente Elias Campo Ola Landgren Francesco Maura mmsig: a fitting approach to accurately identify somatic mutational signatures in hematological malignancies Communications Biology |
| title | mmsig: a fitting approach to accurately identify somatic mutational signatures in hematological malignancies |
| title_full | mmsig: a fitting approach to accurately identify somatic mutational signatures in hematological malignancies |
| title_fullStr | mmsig: a fitting approach to accurately identify somatic mutational signatures in hematological malignancies |
| title_full_unstemmed | mmsig: a fitting approach to accurately identify somatic mutational signatures in hematological malignancies |
| title_short | mmsig: a fitting approach to accurately identify somatic mutational signatures in hematological malignancies |
| title_sort | mmsig a fitting approach to accurately identify somatic mutational signatures in hematological malignancies |
| url | https://doi.org/10.1038/s42003-021-01938-0 |
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