title: Processing, visualising and reconstructing network models from single-cell data.
abstract: New single-cell technologies readily permit gene expression profiling of thousands of cells at single-cell resolution. In this review, we will discuss methods for visualisation and interpretation of single-cell gene expression data, and the computational analysis needed to go from raw data to predictive executable models of gene regulatory network function. We will focus primarily on single-cell real-time quantitative PCR and RNA-sequencing data, but much of what we cover will also be relevant to other platforms, such as the mass cytometry technology for high-dimensional single-cell proteomics.
authors.affiliation: Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK.|Wellcome Trust - Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK.
authors.forename: Steven
authors.initials: S
authors.lastname: Woodhouse
authors.affiliation: Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK.|Wellcome Trust - Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK.
authors.forename: Victoria
authors.initials: V
authors.lastname: Moignard
authors.affiliation: Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK.|Wellcome Trust - Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK.
authors.forename: Berthold
authors.initials: B
authors.lastname: Göttgens
authors.affiliation: Microsoft Research, Cambridge, UK.|Department of Biochemistry, University of Cambridge, Cambridge, UK.
authors.forename: Jasmin
authors.initials: J
authors.lastname: Fisher
mesh_terms: D000818:Animals; D001499:Bayes Theorem; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods; D020869:Gene Expression Profiling / Q000379:methods; D053263:Gene Regulatory Networks; D023281:Genomics / Q000379:methods; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D025341:Principal Component Analysis; D059010:Single-Cell Analysis / Q000379:methods