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Generating realistic null hypothesis of cancer mutational landscapes using SigProfilerSimulator
BACKGROUND: Performing a statistical test requires a null hypothesis. In cancer genomics, a key challenge is the fast generation of accurate somatic mutational landscapes that can be used as a realistic null hypothesis for making biological discoveries. RESULTS: Here we present SigProfilerSimulator,...
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| Опубликовано в: : | BMC Bioinformatics |
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| Главные авторы: | , , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
BioMed Central
2020
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7539472/ https://ncbi.nlm.nih.gov/pubmed/33028213 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-020-03772-3 |
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