title: RT-qPCR work-flow for single-cell data analysis.
abstract: Individual cells represent the basic unit in tissues and organisms and are in many aspects unique in their properties. The introduction of new and sensitive techniques to study single-cells opens up new avenues to understand fundamental biological processes. Well established statistical tools and recommendations exist for gene expression data based on traditional cell population measurements. However, these workflows are not suitable, and some steps are even inappropriate, to apply on single-cell data. Here, we present a simple and practical workflow for preprocessing of single-cell data generated by reverse transcription quantitative real-time PCR. The approach is demonstrated on a data set based on profiling of 41 genes in 303 single-cells. For some pre-processing steps we present options and also recommendations. In particular, we demonstrate and discuss different strategies for handling missing data and scaling data for downstream multivariate analysis. The aim of this workflow is provide guide to the rapidly growing community studying single-cells by means of reverse transcription quantitative real-time PCR profiling.
authors.affiliation: TATAA Biocenter, Gothenburg, Sweden; Sahlgrenska Cancer Center, Department of Pathology, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden. anders.stahlberg@neuro.gu.se
authors.forename: Anders
authors.initials: A
authors.lastname: Ståhlberg
authors.forename: Vendula
authors.initials: V
authors.lastname: Rusnakova
authors.forename: Amin
authors.initials: A
authors.lastname: Forootan
authors.forename: Miroslava
authors.initials: M
authors.lastname: Anderova
authors.forename: Mikael
authors.initials: M
authors.lastname: Kubista
mesh_terms: D000818:Animals; D001253:Astrocytes / Q000378:metabolism; D001921:Brain / Q000098:blood supply / Q000166:cytology; D002545:Brain Ischemia / Q000378:metabolism / Q000473:pathology; D002138:Calibration; D018076:DNA, Complementary / Q000235:genetics; D003627:Data Interpretation, Statistical; D020869:Gene Expression Profiling; D051379:Mice; D025341:Principal Component Analysis; D060888:Real-Time Polymerase Chain Reaction; D020133:Reverse Transcriptase Polymerase Chain Reaction; D059010:Single-Cell Analysis
chemical_list: D018076:DNA, Complementary