Back

Completeness estimation of large-scale single-cell sequencing projects

Miihkinen, M.; Vakkilainen, S.; Aittokallio, T.

2025-01-08 cell biology
10.1101/2025.01.08.631769 bioRxiv
Show abstract

During embryonic development, cells undergo differentiation into highly specialized cell types. Capitalizing on single-cell RNA sequencing, many initiatives and substantial resources have been established for cataloguing these differentiated cell types by their transcriptomic profiles. Despite the extensive efforts to profile various organs and their cellular compositions, we lack metrics to assess the completeness of the sequencing projects. In this cellular biodiversity analysis, we leveraged the increasingly available single-cell data together with statistical methods, originally developed for assessing the species richness of ecological communities, to estimate the cellular diversity of any organ based on current data from single-cell profiling technologies. Deriving from such cellular richness estimates, we established a practical statistical framework that enables reliable assessment of the completeness of any large-scale single-cell profiling projects, after which additional sequencing efforts do not anymore reveal new insights into an organs cellular composition. Such estimates can serve as stoppage-points for the ongoing sequencing projects, hence guiding a more cost-efficient completion of the profiling of various human tissues.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.