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Updated: Jul 29, 2026

Single-cell Gene Expression Profiling Using FACS and qPCR with Internal Standards
Published on: February 25, 2017
Data-driven comparison of multiple high-dimensional single-cell expression profiles
Daigo Okada1, Jian Hao Cheng2, Cheng Zheng2
1Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Nanbusogo-Kenkyu-To-1, 5F, 53 Syogoin-Kawaramachi, Sakyo-ku, Kyoto, 606-8507, Japan. dokada@genome.med.kyoto-u.ac.jp.
Abstract:
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.

