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Expert Review of Molecular Diagnostics Volume 11, 2011 - Issue 7
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Review

Single-cell gene-expression profiling and its potential diagnostic applications

Anders Ståhlberg Sahlgrenska Cancer Center, Department of Pathology, Sahlgrenska Academy at University of Gothenburg, Box 425, 40530 Gothenburg, Sweden; TATAA Biocenter, Odinsgatan 28, 41103 Gothenburg, Sweden;[email protected]
,
Mikael Kubista TATAA Biocenter, Odinsgatan 28, 41103 Gothenburg, Sweden; Institute of Biotechnology, Academy of Sciences of the Czech Republic, Videnska 1083, Prague 4, 14221 Czech Republic; TATAA Biocenter, Odinsgatan 28, 41103 Gothenburg, Sweden; Institute of Biotechnology, Academy of Sciences of the Czech Republic, Videnska 1083, Prague 4, 14221 Czech Republic
&
Pierre Åman Sahlgrenska Cancer Center, Department of Pathology, Sahlgrenska Academy at University of Gothenburg, Box 425, 40530 Gothenburg, Sweden; Sahlgrenska Cancer Center, Department of Pathology, Sahlgrenska Academy at University of Gothenburg, Box 425, 40530 Gothenburg, Sweden
Pages 735-740 | Published online: 09 Jan 2014

Figures & data

Figure 1. Overview of single-cell gene-expression profiling using real-time quantitative PCR.
Figure 1. Overview of single-cell gene-expression profiling using real-time quantitative PCR.
Figure 2. Single-cell gene-expression data.

Relative expression of fusion transcript FUSDDIT3 in 88 single myxoid/round cell liposarcoma cells (A). Distribution of FUSDDIT3 in linear (B) and log10(C) scales.

Data taken from [Ståhlberg A et al., Unpublished Data].

Figure 2. Single-cell gene-expression data.Relative expression of fusion transcript FUSDDIT3 in 88 single myxoid/round cell liposarcoma cells (A). Distribution of FUSDDIT3 in linear (B) and log10(C) scales.Data taken from [Ståhlberg A et al., Unpublished Data].
Figure 3. Cell heterogeneity.

Single-cell analysis allows identification and characterization of different cell types (A) and studies of heterogeneity within respective cell types (B).

Figure 3. Cell heterogeneity.Single-cell analysis allows identification and characterization of different cell types (A) and studies of heterogeneity within respective cell types (B).

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