TY - CHAP
T1 - Heterogeneity of metazoan cells and beyond
T2 - To integrative analysis of cellular populations at single-cell level
AU - Barteneva, Natalie
AU - Vorobyev, Ivan
PY - 2018/1/1
Y1 - 2018/1/1
N2 - In this paper, we review some of the recent advances in cellular heterogeneity and single-cell analysis methods. In modern research of cellular heterogeneity, there are four major approaches: analysis of pooled samples, single-cell analysis, high-throughput single-cell analysis, and lately integrated analysis of cellular population at a single-cell level. Recently developed high-throughput single-cell genetic analysis methods such as RNA-Seq require purification step and destruction of an analyzed cell often are providing a snapshot of the investigated cell without spatiotemporal context. Correlative analysis of multiparameter morphological, functional, and molecular information is important for differentiation of more uniform groups in the spectrum of different cell types. Simplified distributions (histograms and 2D plots) can underrepresent biologically significant subpopulations. Future directions may include the development of nondestructive methods for dissecting molecular events in intact cells, simultaneous correlative cellular analysis of phenotypic and molecular features by hybrid technologies such as imaging flow cytometry, and further progress in supervised and non-supervised statistical analysis algorithms.
AB - In this paper, we review some of the recent advances in cellular heterogeneity and single-cell analysis methods. In modern research of cellular heterogeneity, there are four major approaches: analysis of pooled samples, single-cell analysis, high-throughput single-cell analysis, and lately integrated analysis of cellular population at a single-cell level. Recently developed high-throughput single-cell genetic analysis methods such as RNA-Seq require purification step and destruction of an analyzed cell often are providing a snapshot of the investigated cell without spatiotemporal context. Correlative analysis of multiparameter morphological, functional, and molecular information is important for differentiation of more uniform groups in the spectrum of different cell types. Simplified distributions (histograms and 2D plots) can underrepresent biologically significant subpopulations. Future directions may include the development of nondestructive methods for dissecting molecular events in intact cells, simultaneous correlative cellular analysis of phenotypic and molecular features by hybrid technologies such as imaging flow cytometry, and further progress in supervised and non-supervised statistical analysis algorithms.
KW - Cellular heterogeneity
KW - Cellular profiling
KW - Cluster analysis
KW - Imaging flow cytometry
KW - Mass cytometry
KW - Phenotypic heterogeneity
KW - RNA-sequencing
KW - Single-cell analysis
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U2 - 10.1007/978-1-4939-7680-5_1
DO - 10.1007/978-1-4939-7680-5_1
M3 - Chapter
AN - SCOPUS:85042559424
T3 - Methods in Molecular Biology
SP - 3
EP - 23
BT - Methods in Molecular Biology
PB - Humana Press Inc.
ER -