Zappia, Luke

Opportunities and challenges in long-read sequencing data analysis

Amarasinghe, S. L., Su, S., Dong, X., Zappia, L., Ritchie, M. E., & Gouil, Q. (2020) · Genome Biology

Genomics and Phylogenetic StudiesSingle-cell and spatial transcriptomics

Cited by 2,530

Benchmarking atlas-level data integration in single-cell genomics

Luecken, M. D., Büttner, M., Chaichoompu, K., Danese, A., Interlandi, M., Mueller, M. F., Strobl, D. C., Zappia, L., Dugas, M., Colomé-Tatché, M., et al. (2022) · Nature Methods

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 1,438

Clustering trees: a visualization for evaluating clusterings at multiple resolutions

Zappia, L., & Oshlack, A. (2018) · GigaScience

Advanced Clustering Algorithms ResearchData Visualization and Analytics

Cited by 1,064

Best practices for single-cell analysis across modalities

Heumos, L., Schaar, A. C., Lance, C., Litinetskaya, A., Drost, F., Zappia, L., Lücken, M. D., Strobl, D. C., Henao, J., Curion, F., et al. (2023) · Nature Reviews Genetics

Single-cell and spatial transcriptomicsBioinformatics and Genomic Networks

Cited by 1,051

Splatter: simulation of single-cell RNA sequencing data

Zappia, L., Phipson, B., & Oshlack, A. (2017) · Genome Biology

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 905

Gene length and detection bias in single cell RNA sequencing protocols

Phipson, B., Zappia, L., & Oshlack, A. (2017) · F1000Research

Single-cell and spatial transcriptomicsGenomics and Phylogenetic Studies

Cited by 74

Sfaira accelerates data and model reuse in single cell genomics

Fischer, D. S., Dony, L., König, M., Moeed, A., Zappia, L., Heumos, L., Tritschler, S., Holmberg, O., Aliee, H., & Theis, F. J. (2021) · Genome Biology

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 33