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Acknowledgements
The authors are grateful to A. Sato, M. Matsumura, K. Yin, and F. Saito for their excellent technical assistance. The authors also wish to express their appreciation to K. Chiba, and H. Tanaka (The University of Tokyo) for the supercomputer. This work was supported by KAKENHI grant numbers 17H04224 (JT) and 15H05909, JP26221308, and JP19H05656 (SO) from the Japan Society of Promotion of Science, by Japan Agency for Medical Research and Development (AMED) Practical Research for Innovative Cancer Control and Project for Cancer Research and Therapeutic Evolution (P-CREATE) (16cm0106509h001 (JT), and by the Friends of Leukemia Research Fund (SK). This research also used the computational resources of the K computer provided by the RIKEN Advanced Institute for Computational Science through the HPCI System Research project (hp140230, hp160219, and hp150232) (SM and SO).
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Contribution: SK and JT wrote the paper; SK, MS, KY, TI, YN, HU, and M. Sanada analyzed the data; MK, KK, RK, YH, TI, AS, NK, AM, AO, and KH collected the data and samples; SK, MS, TK, HG, KO, TD, NK, MM, and KH performed the experiments; YS, HS, YS, and SM developed the bioinformatics pipelines; MK, AO, YH, SO, and JT gave conceptual advice; JT designed the study. All authors read and approved the final paper.
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Kimura, S., Seki, M., Kawai, T. et al. DNA methylation-based classification reveals difference between pediatric T-cell acute lymphoblastic leukemia and normal thymocytes. Leukemia 34, 1163–1168 (2020). https://doi.org/10.1038/s41375-019-0626-2
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DOI: https://doi.org/10.1038/s41375-019-0626-2
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