Jingyi Jessica Li | Statistical Rigor in Genomics Data Science

Jingyi Jessica Li | Statistical Rigor in Genomics Data Science
Related papers:
1. Li, Y., Ge, X., Peng, F., Li, W., & Li, J. J. (2022). Exaggerated false positives by popular differential expression methods when analyzing human population samples. Genome biology, 23(1), 79. doi.org/10.118...
2. Song, D., & Li, J. J. (2021). PseudotimeDE: inference of differential gene expression along cell pseudotime with well-calibrated p-values from single-cell RNA sequencing data. Genome biology, 22(1), 124. doi.org/10.118...
3. Ge, X., Chen, Y. E., Song, D., McDermott, M., Woyshner, K., Manousopoulou, A., Wang, N., Li, W., Wang, L. D., & Li, J. J. (2021). Clipper: p-value-free FDR control on high-throughput data from two conditions. Genome biology, 22(1), 288. doi.org/10.118...
4. Sun, T., Song, D., Li, W. V., & Li, J. J. (2021). scDesign2: a transparent simulator that generates high-fidelity single-cell gene expression count data with gene correlations captured. Genome biology, 22(1), 163. doi.org/10.118...
5. Sun, T., Song, D., Li, W. V., & Li, J. J. (2022). Simulating Single-Cell Gene Expression Count Data with Preserved Gene Correlations by scDesign2. Journal of computational biology : a journal of computational molecular cell biology, 29(1), 23-26. doi.org/10.108...
6. Li, J. J., & Tong, X. (2020). Statistical Hypothesis Testing versus Machine Learning Binary Classification: Distinctions and Guidelines. Patterns (New York, N.Y.), 1(7), 100115. doi.org/10.101...