Design and Analysis of Single-Cell Sequencing Experiments | Zendy

Dominic Grün | Zendy; Alexander van Oudenaarden | Zendy

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Design and Analysis of Single-Cell Sequencing Experiments

Author(s) -

Dominic Grün,

Alexander van Oudenaarden

Publication year - 2015

Publication title -

cell

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 26.304

H-Index - 776

eISSN - 1097-4172

pISSN - 0092-8674

DOI - 10.1016/j.cell.2015.10.039

Subject(s) - biology , single cell sequencing , computational biology , dna sequencing , single cell analysis , leverage (statistics) , cancer genome sequencing , genomics , genome , somatic cell , deep sequencing , genetics , cell , reference genome , dna , exome sequencing , gene , mutation , computer science , machine learning

Recent advances in single-cell sequencing hold great potential for exploring biological systems with unprecedented resolution. Sequencing the genome of individual cells can reveal somatic mutations and allows the investigation of clonal dynamics. Single-cell transcriptome sequencing can elucidate the cell type composition of a sample. However, single-cell sequencing comes with major technical challenges and yields complex data output. In this Primer, we provide an overview of available methods and discuss experimental design and single-cell data analysis. We hope that these guidelines will enable a growing number of researchers to leverage the power of single-cell sequencing.

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