Počet záznamů: 1
RT-qPCR work-flow for single-cell data analysis
- 1.0392069 - BTÚ 2014 RIV US eng J - Článek v odborném periodiku
Stahlberg, A. - Rusňáková, Vendula - Forootan, A. - Anděrová, Miroslava - Kubista, Mikael
RT-qPCR work-flow for single-cell data analysis.
Methods. Roč. 59, č. 1 (2013), s. 80-88. ISSN 1046-2023. E-ISSN 1095-9130
Grant CEP: GA MŠMT(CZ) ME10052; GA ČR GAP303/10/1338
Výzkumný záměr: CEZ:AV0Z50520701
Institucionální podpora: RVO:68378041
Klíčová slova: RT-qPCR * Single-cell biology * Single-cell data analysis
Kód oboru RIV: EB - Genetika a molekulární biologie; FH - Neurologie, neurochirurgie, neurovědy (UEM-P)
Impakt faktor: 3.221, rok: 2013
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. (C) 2012 Elsevier Inc. All rights reserved.
Trvalý link: http://hdl.handle.net/11104/0221033
Počet záznamů: 1