Last updated: 2019-04-03

workflowr checks: (Click a bullet for more information)
Expand here to see past versions:

Expand here to see past versions of organoid-black.png:
Version Author Date
33ac14f Luke Zappia 2019-03-20


This website displays the analysis code and results for the analysis chapter of my PhD thesis. In this chapter I reanalyse a previously published kidney organoid scRNA-seq dataset (Phipson et al. 2019; Combes et al. 2019), focusing on the decisions that are made during analysis and demonstrating a range of tools that can be used for various tasks.

Follow the links below to access the different stages of analysis or refer to the Getting started page for more details about the dataset and how to reproduce the analysis.


Methods - Description of methods used during the analysis.


This website and the analysis code can be cited as:

Zappia, Luke. PhD thesis analysis. 2019. DOI: 10.5281/zenodo.2622384

This data files associated with this analysis can be cited as:

Zappia L. PhD thesis analysis data. University of Melbourne. 2019. DOI: 10.26188/5c9182aa7e23d

If you use this data in an analysis please cite the publcations that originally described it.


Combes, Alexander N, Luke Zappia, Pei Xuan Er, Alicia Oshlack, and Melissa H Little. 2019. “Single-cell analysis reveals congruence between kidney organoids and human fetal kidney.” Genome Medicine 11 (1): 3. doi:10.1186/s13073-019-0615-0.

Phipson, Belinda, Pei X Er, Alexander N Combes, Thomas A Forbes, Sara E Howden, Luke Zappia, Hsan-Jan Yen, et al. 2019. “Evaluation of variability in human kidney organoids.” Nature Methods 16 (1): 79–87. doi:10.1038/s41592-018-0253-2.


This reproducible R Markdown analysis was created with workflowr 1.1.1