Software for tumor clonal classification
2017
Washington University School of Medicine, Saint Louis, USA
Software is developed to overcome the error rates in clonal ordering in the study of tumour progression. Using a bootstrap resampling technique, that takes into account statistical variability, it is possible to identify the sample origin and subclones. This method outperformed three other widely used tools and was able to identify and classify subclones in different clinical samples of leukaemia and breast cancer; showing the potential to monitor clonal populations in tumour biopsies or to guide personalised medicine.
ClonEvol: clonal ordering and visualization in cancer sequencing
Christopher A Maher
Added on: 07-28-2021
[1] https://www.annalsofoncology.org/article/S0923-7534(19)35385-2/fulltext[2] https://data.jrc.ec.europa.eu/dataset/ffebe454-ed9a-47cf-8a33-8cf70c1b7d38
