Open this publication in new window or tab >>Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.
Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences.
Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences.
Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular Precision Medicine. Uppsala University, Science for Life Laboratory, SciLifeLab.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences. Uppsala University, Science for Life Laboratory, SciLifeLab.
Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Cancer precision medicine. Uppsala University, Science for Life Laboratory, SciLifeLab.
Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences. Uppsala University, Science for Life Laboratory, SciLifeLab.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.
Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Genomics and Neurobiology.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences. Uppsala University, Science for Life Laboratory, SciLifeLab.
Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular Precision Medicine.
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2023 (English)In: BMC Research Notes, E-ISSN 1756-0500, Vol. 16, no 1, article id 265Article in journal (Refereed) Published
Abstract [en]
Objectives
The aim of this data paper is to describe a collection of 33 genomic, transcriptomic and epigenomic sequencing datasets of the B-cell acute lymphoblastic leukemia (ALL) cell line REH. REH is one of the most frequently used cell lines for functional studies of pediatric ALL, and these data provide a multi-faceted characterization of its molecular features. The datasets described herein, generated with short- and long-read sequencing technologies, can both provide insights into the complex aberrant karyotype of REH, and be used as reference datasets for sequencing data quality assessment or for methods development.
Data description
This paper describes 33 datasets corresponding to 867 gigabases of raw sequencing data generated from the REH cell line. These datasets include five different approaches for whole genome sequencing (WGS) on four sequencing platforms, two RNA sequencing (RNA-seq) techniques on two different sequencing platforms, DNA methylation sequencing, and single-cell ATAC-sequencing.
Place, publisher, year, edition, pages
BioMed Central (BMC), 2023
National Category
Cancer and Oncology Cell and Molecular Biology
Identifiers
urn:nbn:se:uu:diva-516199 (URN)10.1186/s13104-023-06537-2 (DOI)001082017600002 ()37817248 (PubMedID)
Funder
Uppsala UniversitySwedish Research Council, 2019-01976Swedish Research Council, 2019-0222Swedish Childhood Cancer Foundation, 2019-0046Swedish Childhood Cancer Foundation, 2022-0086Göran Gustafsson Foundation for promotion of scientific research at Uppala University and Royal Institute of TechnologyEU, Horizon 2020, 824110
2023-11-172023-11-172024-01-17Bibliographically approved