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Sincast: a computational framework to predict cell identities in single cell transcriptomes using bulk atlases as references
[article]
2021
bioRxiv
pre-print
Characterizing the molecular identity of a cell is an essential step in single cell RNA-sequencing (scRNA-seq) data analysis. Numerous tools exist for predicting cell identity using single cell reference atlases. However, many challenges remain, including correcting for inherent batch effects between reference and query data and insufficient phenotype data from the reference. One solution is to project single cell data onto established bulk reference atlases to leverage their rich phenotype
doi:10.1101/2021.11.07.467660
fatcat:du2mgy3sqvaddbue2hefgakuce