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Identifying genes and cell types with dynamic alternative polyadenylation in multi-cluster single-cell transcriptomics data
YuLong Bai, Yidi Qin, Soyeon Kim, Zhenjiang Fan, KyongNyon Nam, Radosveta Koldamova, Quasar Saleem Padiath, Hyun Jung Park
doi: https://doi.org/10.1101/2020.07.30.229096
YuLong Bai
1Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States
Yidi Qin
1Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States
Soyeon Kim
2Department of Pediatrics, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
3Division of Pulmonary Medicine, Children’s Hospital of Pittsburgh of UPMC, Pittsburgh, Pennsylvania, USA
Zhenjiang Fan
4Department of Computer Science, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
KyongNyon Nam
5Department of Environmental and Occupational Health, Graduate school of Public Health, University of Pittsburgh, Pennsylvania, USA
Radosveta Koldamova
5Department of Environmental and Occupational Health, Graduate school of Public Health, University of Pittsburgh, Pennsylvania, USA
Quasar Saleem Padiath
1Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States
6Department of Neurobiology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
Hyun Jung Park
1Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States
Article usage
Posted July 31, 2020.
Identifying genes and cell types with dynamic alternative polyadenylation in multi-cluster single-cell transcriptomics data
YuLong Bai, Yidi Qin, Soyeon Kim, Zhenjiang Fan, KyongNyon Nam, Radosveta Koldamova, Quasar Saleem Padiath, Hyun Jung Park
bioRxiv 2020.07.30.229096; doi: https://doi.org/10.1101/2020.07.30.229096
Identifying genes and cell types with dynamic alternative polyadenylation in multi-cluster single-cell transcriptomics data
YuLong Bai, Yidi Qin, Soyeon Kim, Zhenjiang Fan, KyongNyon Nam, Radosveta Koldamova, Quasar Saleem Padiath, Hyun Jung Park
bioRxiv 2020.07.30.229096; doi: https://doi.org/10.1101/2020.07.30.229096
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