Kinsey Van Deynze
University of California, San Diego
5 Papers
3 Citations
Kinsey Van Deynze is an academic researcher from University of California, San Diego. The author has contributed to research in topics: Computer science & Cancer research. The author has an hindex of 1, co-authored 2 publications.
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Papers
Integrated analysis of single-cell chromatin state and transcriptome identified common vulnerability despite glioblastoma heterogeneity.
Ramya Raviram,Anugraha M. Raman,Sebastian Preissl,Tomoyuki Koga,Kai Zhang,Cameron Brennan,Chenxu Zhu,Jens Luebeck,Kinsey Van Deynze,Jee Yun Han,Xiaomeng Hou,Zhen Ye,Anna K Mischel,Yang Eric Li,Rongxin Fang,Tomas Baback,Joshua W. Mugford,Claudia Z. Han,Christopher K. Glass,Cathy L. Barr,Paul S. Mischel,Vineet Bafna,Laure Escoubet,Bing Ren,Clark C. Chen +24 more
TL;DR: In 2019, the World Health Organization as mentioned in this paper reclassified glioblastoma, the most common form of adult brain cancer, into isocitrate dehydrogenase (IDH)-wild-type (G4-IDH mutant) and grade IV IDH mutant (G 4 IDHm) astrocytomas, and showed that despite differences in IDH mutation status and significant intratumoral heterogeneity, the profiled tumor cells shared a common chromatin structure defined by open regions enriched for nuclear factor 1 transcription factors.
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HiC-DC+: systematic 3D interaction calls and differential analysis for Hi-C and HiChIP
TL;DR: Differential HiC-DC+ analysis recovered global principles of 3D organization during cohesin perturbation and differentiation, including TAD aggregation, enhancer hubs, and promoter-enhancer loop dynamics.
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Enhanced Detection and Genotyping of Disease-Associated Tandem Repeats Using HMMSTR and Targeted Long-Read Sequencing
Kinsey Van Deynze,Camille Mumm,Connor J. Maltby,Jessica A. Switzenberg,Peter K. Todd,Alan P. Boyle +5 more
TL;DR: Researchers developed a targeted nanopore sequencing panel and HMMSTR algorithm to accurately detect and genotype disease-associated tandem repeats, outperforming current methods and identifying unexpected expansions in patient-derived samples with high accuracy and scalability.
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Dddr-24. integrated analysis of single cell chromatin accessibility and rna expression identified common vulnerability despite glioblastoma heterogeneity
Ramya Raviram,Anugraha M. Raman,Sebastian Preissl,Shaoping Wu,Tomoyuki Koga,Chenxu Zhu,Jens Luebeck,Kinsey Van Deynze,Jee Yun Han,Xioameng Hou,Zhen Ye,Anna K Mischel,Yang Eric Li,Rongxin Fang,Tomas Baback,Joshua W. Mugford,Claudia Z. Han,Christopher K. Glass,Cathy Barr,Paul S. Mischel,Vineet Bafna,Laura Escoubet,Bing Ren,Cl Chen +23 more
TL;DR: This paper applied integrated genome-wide chromatin accessibility (snATACseq) and transcription profiles to clinical specimens derived IDHwt glioblastomas and G4 IDHm astrocytomas, with goal of therapeutic target discovery.
HiC-DC+ enables systematic 3D interaction calls and differential analysis for Hi-C and HiChIP.
TL;DR: HiC-DC+ as discussed by the authors is a software tool for Hi-C/HiChIP interaction calling and differential analysis using an efficient implementation of the HiC-dc statistical framework, which integrates with popular preprocessing and visualization tools and includes topologically associating domain (TAD) and A/B compartment callers.