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Dongyuan Song

Showing results (1-10 of 30) with videos related to

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Genome Biology|April 30, 2021
PseudotimeDE: inference of differential gene expression along cell pseudotime with well-calibrated p-values from single-cell RNA sequencing dataDongyuan Song, Jingyi Jessica Li
BMC Genomics|June 5, 2026
Evaluating the learnability of single-cell large language models on multiple tasksYu Yan, Xutao Wang, Dongyuan Song
Nature Communications|November 19, 2023
scReadSim: a single-cell RNA-seq and ATAC-seq read simulatorGuanao Yan, Dongyuan Song, Jingyi Jessica Li
Research Square|August 14, 2023
ClusterDE: a post-clustering differential expression (DE) method robust to false-positive inflation caused by double dippingDongyuan Song, Kexin Li, Xinzhou Ge, et al.
Journal of the American Statistical Association|June 2, 2025
Comment on "Data Fission: Splitting a Single Data Point", Data Fission for Unsupervised Learning: A Discussion on Post-Clustering Inference and the Challenges of DebiasingChanghu Wang, Xinzhou Ge, Dongyuan Song, et al.
Bioinformatics (Oxford, England)|October 21, 2025
PseudotimeDE-fast: fast testing of differential gene expression along cell pseudotimeYuheng Lai, Dongyuan Song, Lucy Xia, et al.
Genome Biology|January 22, 2022
Statistics or biology: the zero-inflation controversy about scRNA-seq dataRuochen Jiang, Tianyi Sun, Dongyuan Song, et al.
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology|October 8, 2025
ClusterDE: A Statistical Software Package for Removing Double-Dipping Bias in Post-Clustering Differential Expression AnalysisChristy Lee, Dongyuan Song, Siqi Chen, et al.
Biorxiv : the Preprint Server for Biology|March 11, 2026
scDesignPop generates realistic population-scale single-cell RNA-seq for power analysis, benchmarking, and privacy protectionChris Y Dong, Yihui Cen, Dongyuan Song, et al.
Genome Biology|June 10, 2021
Publisher Correction: scDesign2: a transparent simulator that generates high-fidelity single-cell gene expression count data with gene correlations capturedTianyi Sun, Dongyuan Song, Wei Vivian Li, et al.
Pageof 3

Showing results (1-10 of 30) with videos related to

Sort By:
Pageof 3
Genome Biology|April 30, 2021
PseudotimeDE: inference of differential gene expression along cell pseudotime with well-calibrated p-values from single-cell RNA sequencing dataDongyuan Song, Jingyi Jessica Li
BMC Genomics|June 5, 2026
Evaluating the learnability of single-cell large language models on multiple tasksYu Yan, Xutao Wang, Dongyuan Song
Nature Communications|November 19, 2023
scReadSim: a single-cell RNA-seq and ATAC-seq read simulatorGuanao Yan, Dongyuan Song, Jingyi Jessica Li
Research Square|August 14, 2023
ClusterDE: a post-clustering differential expression (DE) method robust to false-positive inflation caused by double dippingDongyuan Song, Kexin Li, Xinzhou Ge, et al.
Journal of the American Statistical Association|June 2, 2025
Comment on "Data Fission: Splitting a Single Data Point", Data Fission for Unsupervised Learning: A Discussion on Post-Clustering Inference and the Challenges of DebiasingChanghu Wang, Xinzhou Ge, Dongyuan Song, et al.
Bioinformatics (Oxford, England)|October 21, 2025
PseudotimeDE-fast: fast testing of differential gene expression along cell pseudotimeYuheng Lai, Dongyuan Song, Lucy Xia, et al.
Genome Biology|January 22, 2022
Statistics or biology: the zero-inflation controversy about scRNA-seq dataRuochen Jiang, Tianyi Sun, Dongyuan Song, et al.
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology|October 8, 2025
ClusterDE: A Statistical Software Package for Removing Double-Dipping Bias in Post-Clustering Differential Expression AnalysisChristy Lee, Dongyuan Song, Siqi Chen, et al.
Biorxiv : the Preprint Server for Biology|March 11, 2026
scDesignPop generates realistic population-scale single-cell RNA-seq for power analysis, benchmarking, and privacy protectionChris Y Dong, Yihui Cen, Dongyuan Song, et al.
Genome Biology|June 10, 2021
Publisher Correction: scDesign2: a transparent simulator that generates high-fidelity single-cell gene expression count data with gene correlations capturedTianyi Sun, Dongyuan Song, Wei Vivian Li, et al.
Pageof 3