DevKidCC allows for robust classification and direct comparisons of kidney organoid datasets.

ABSTRACT:

Background

While single-cell transcriptional profiling has greatly increased our capacity to interrogate biology, accurate cell classification within and between datasets is a key challenge. This is particularly so in pluripotent stem cell-derived organoids which represent a model of a developmental system. Here, clustering algorithms and selected marker genes can fail to accurately classify cellular identity while variation in analyses makes it difficult to meaningfully compare datasets. Kidney organoids provide a valuable resource to understand kidney development and disease. However, direct comparison of relative cellular composition between protocols has proved challenging. Hence, an unbiased approach for classifying cell identity is required.

Methods

The R package, scPr

SUBMITTER: Wilson SB 

PROVIDER: S-EPMC8862535 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature