PT  - JOURNAL ARTICLE
AU  - Vinay S Swamy
AU  - Temesgen D Fufa
AU  - Robert B Hufnagel
AU  - David M McGaughey
TI  - Building the Mega Single Cell Transcriptome Ocular Meta-Atlas
AID  - 10.1101/2021.03.26.437190
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2021.03.26.437190
4099  - http://biorxiv.org/content/early/2021/03/28/2021.03.26.437190.short
4100  - http://biorxiv.org/content/early/2021/03/28/2021.03.26.437190.full
AB  - The development of highly scalable single cell transcriptome technology has resulted in the creation of thousands of datasets, over 30 in the retina alone. Analyzing the transcriptomes between different projects is highly desirable as this would allow for better assessment of which biological effects are consistent across independent studies. However it is difficult to compare and contrast data across different projects as there are substantial batch effects from computational processing, single cell technology utilized, and the natural biological variation. While many single cell transcriptome specific batch correction methods purport to remove the technical noise it is difficult to ascertain which method functions works best. We developed a lightweight R package (scPOP) that brings in batch integration methods and uses a simple heuristic to balance batch merging and celltype/cluster purity. We use this package along with a Snakefile based workflow system to demonstrate how to optimally merge 766,615 cells from 34 retina datsets and three species to create a massive ocular single cell transcriptome meta-atlas. This provides a model how to efficiently create meta-atlases for tissues and cells of interest.Competing Interest StatementThe authors have declared no competing interest.