Data exploration, quality control and testing in single-cell qPCR-based gene expression experiments | Zendy

Andrew McDavid | Zendy; Greg Finak | Zendy; Pratip K. Chattopadyay | Zendy; María Domínguez | Zendy; Laurie Lamoreaux | Zendy; Schmidt Steven | Zendy; Mario Roederer | Zendy; Raphaël Gottardo | Zendy

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Data exploration, quality control and testing in single-cell qPCR-based gene expression experiments

Author(s) -

Andrew McDavid,

Greg Finak,

Pratip K. Chattopadyay,

María Domínguez,

Laurie Lamoreaux,

Schmidt Steven,

Mario Roederer,

Raphaël Gottardo

Publication year - 2012

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/bts714

Subject(s) - computer science , expression (computer science) , parametric statistics , computational biology , statistical hypothesis testing , data mining , biology , statistics , mathematics , programming language

Cell populations are never truly homogeneous; individual cells exist in biochemical states that define functional differences between them. New technology based on microfluidic arrays combined with multiplexed quantitative polymerase chain reactions now enables high-throughput single-cell gene expression measurement, allowing assessment of cellular heterogeneity. However, few analytic tools have been developed specifically for the statistical and analytical challenges of single-cell quantitative polymerase chain reactions data.

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