Publikationsdatum:
2021-11-01
Beschreibung:
Comparing multiple single-cell expression datasets such as cytometry and scRNA-seq data between case and control donors provides information to elucidate the mechanisms of disease. We propose a completely data-driven computational biological method for this task. This overcomes the challenges of conventional cellular subset-based comparisons and facilitates further analyses such as machine learning and gene set analysis of single-cell expression datasets.
Print ISSN:
1434-5161
Digitale ISSN:
1435-232X
Thema:
Biologie
,
Medizin
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