Link to bioRxiv paper:
http://biorxiv.org/cgi/content/short/2023.03.12.532317v1?rss=1
Authors: Chin, W. L., Portes dos Santos, L., Small, M., Lesterhuis, W. J., Lassmann, T.
Abstract:
Single cell RNA sequencing is an ubiquitous method for studying changes in cellular states within and across conditions. Differential expression (DE) analysis may miss subtle differ- ences, especially where transcriptional variability is not unique to a specific condition, but shared across multiple conditions or phenotypes. Here, we present CDR-g (Concatenate- Decompose-Rotate genomics), a fast and scalable strategy based on spectral factorisation of gene coexpression matrices. CDR-g detects subtle changes in gene coexpression across a continuum of biological states in multi-condition single cell data. CDR-g collates these changes and builds a detailed profile of differential cell states. Applying CDR-g, we show that it identifies biological pathways not detected using conventional DE analysis and de- lineates novel, condition-specific subpopulations in single-cell datasets.
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