RT-qPCR work-flow for single-cell data analysis.
Methods
; 59(1): 80-8, 2013 Jan.
Article
em En
| MEDLINE
| ID: mdl-23021995
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.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Reação em Cadeia da Polimerase Via Transcriptase Reversa
/
Perfilação da Expressão Gênica
/
Análise de Célula Única
/
Reação em Cadeia da Polimerase em Tempo Real
Tipo de estudo:
Guideline
Limite:
Animals
Idioma:
En
Ano de publicação:
2013
Tipo de documento:
Article