Journal article
Sincast: a computational framework to predict cell identities in single-cell transcriptomes using bulk atlases as references
Y Deng, J Choi, KAL Cao
Briefings in Bioinformatics | Published : 2022
DOI: 10.1093/bib/bbac088
Abstract
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 andinsufficient phenotype data from the reference. One solution is to project single-cell data onto established bulk reference atlases to leverage their rich phenotype information. Sincast is a computational framework to query scRNA-seq data by projection onto bulk reference atlases. Prior to projection, single-cell data are transformed to be directly comparable to bulk ..
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Awarded by Australian Research Council
Funding Acknowledgements
National Health and Medical Research Council (NHMRC) Career Development Fellowship (GNT1159458); Australian Research Council Discovery Project (DP200102903).