RNAseq Analysis Seurat Code - Bioprinted 3D Outer Retina Barrier Uncovers RPE-dependent Choroidal Phenotype in Advanced Macular Degeneration - Nature Methods
Creators
- Song, Min Jae1
- Quinn, Russ2
- Nguyen, Eric2
- Hampton, Christopher2
- Sharma, Ruchi2
- Park, Tea Soon2
- Koster, Céline3
- Voss, Ty4
- Tristan, Carlos4
- Singh, Anju4
- Dejene, Roba2
- Bose, Devika2
- Chen, Yu-Chi4
- Derr, Paige4
- Derr, Kristy4
- Michael, Sam4
- Barone, Francesca2
- Chen, Guibin5
- Boehm, Manfred5
- Maminishkis, Arvydas2
- Singec, Ilyas4
- Ferrer, Marc4
- Bharti, Kapil1
- 1. National Eye Institute, National Institutes of Health; National Center for Advancing Translational Sciences, National Institutes of Health
- 2. National Eye Institute, National Institutes of Health
- 3. Department of Clinical Genetics, Amsterdam University Medical Centers (AUMC)
- 4. National Center for Advancing Translational Sciences, National Institutes of Health
- 5. National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH)
Description
R Code for analyzing RNAseq data included in the Nature Methods Publication, "Bioprinted 3D Outer Retina Barrier Uncovers RPE-dependent Choroidal Phenotype in Advanced Macular Degeneration".
Code requires a large Seurat file input, preferably with cell type or tissue culture method idents already assigned to samples. The example used in our data analysis is included here as "RPE_f4_SCT FIRST.rdata". The code will separate cells from the original Seurat file by sample idents, perform clustering analysis on uncategorized cell types (i.e. non-enriched cells from 3D-bioprinted tissues), perform differential expression analysis and average expression analysis per gene, produce dot plots and feature plots of significantly upregulated and downregulated genes, and create average expression heatmaps for comparison with gene lists in literature.
RAM requirements depend on the size of the large Seurat file input. Processing the included Seurat file will require 256 GB of RAM.