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Design and Analysis of Single-Cell Sequencing Experiments.
Literature Information
| PMID | 26544934 |
|---|---|
| Journal | Cell |
| Impact Factor | 42.5 |
| JCR Quartile | Q1 |
| Publication Year | 2015 |
| Times Cited | 262 |
| Keywords | single-cell sequencing, experimental design, data analysis |
| Literature Type | Journal Article, Review |
| ISSN | 0092-8674 |
| Pages | 799-810 |
| Issue | 163(4) |
| Authors | Dominic Grün, Alexander van Oudenaarden |
TL;DR
This Primer reviews recent advancements in single-cell sequencing, highlighting its potential to uncover somatic mutations and cell type composition while addressing the significant technical challenges and complex data outputs associated with these methods. By providing an overview of available techniques and guidelines for experimental design and data analysis, the authors aim to empower researchers to effectively utilize single-cell sequencing in their studies of biological systems.
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single-cell sequencing · experimental design · data analysis
Abstract
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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Primary Questions Addressed
- What are the most common technical challenges faced in single-cell sequencing experiments?
- How do different methods of single-cell sequencing compare in terms of data output and analysis?
- What are the best practices for designing experiments that utilize single-cell transcriptome sequencing?
- How can researchers effectively analyze the complex data generated from single-cell sequencing?
- What role do somatic mutations play in understanding clonal dynamics through single-cell sequencing?
Key Findings
Key Insights
Research Background and Purpose: The study focuses on the emerging field of single-cell sequencing, which offers unprecedented insights into biological systems by allowing researchers to analyze the genome and transcriptome of individual cells. This capability is crucial for understanding complex biological phenomena, such as the heterogeneity within cell populations, the dynamics of clonal evolution, and the intricate interplay of various cell types within tissues. The primary goal of the research is to provide comprehensive guidelines for experimental design and data analysis in single-cell sequencing, thereby facilitating its adoption among a broader range of researchers.
Main Methods and Findings: The Primer reviews the current methodologies available for single-cell sequencing, including both genomic and transcriptomic approaches. It emphasizes the importance of selecting appropriate techniques based on the biological questions posed. The findings highlight the technical challenges associated with single-cell sequencing, such as the generation of high-quality data and the complexity of data interpretation. The authors outline best practices for experimental design, including considerations for sample preparation, library construction, and sequencing platforms. They also address the intricacies of data analysis, emphasizing the need for robust computational tools to handle the high dimensionality and noise inherent in single-cell datasets.
Core Conclusions: The authors conclude that while single-cell sequencing presents significant technical challenges, its potential to transform our understanding of biology is immense. They advocate for the establishment of standardized protocols and analytical frameworks to enhance reproducibility and facilitate the interpretation of results. The guidelines provided aim to empower researchers to effectively utilize single-cell sequencing technologies to uncover novel biological insights and to improve the clarity of their findings.
Research Significance and Impact: The significance of this research lies in its potential to democratize access to single-cell sequencing technologies, thereby broadening the scope of biological research. By equipping researchers with the necessary tools and knowledge, the Primer aims to accelerate discoveries in fields such as cancer biology, immunology, and developmental biology. The impact of this work is likely to be profound as it encourages innovative applications of single-cell analysis, leading to a deeper understanding of cellular heterogeneity and disease mechanisms. Ultimately, the insights derived from single-cell sequencing could pave the way for new therapeutic strategies and personalized medicine approaches that are tailored to individual cellular profiles.
Literatures Citing This Work
- Single neuron transcriptome analysis can reveal more than cell type classification: Does it matter if every neuron is unique? - Lise J Harbom;William D Chronister;Michael J McConnell - BioEssays : news and reviews in molecular, cellular and developmental biology (2016)
- Highly multiplexed simultaneous detection of RNAs and proteins in single cells. - Andreas P Frei;Felice-Alessio Bava;Eli R Zunder;Elena W Y Hsieh;Shih-Yu Chen;Garry P Nolan;Pier Federico Gherardini - Nature methods (2016)
- Linking the T cell receptor to the single cell transcriptome in antigen-specific human T cells. - Auda A Eltahla;Simone Rizzetto;Mehdi R Pirozyan;Brigid D Betz-Stablein;Vanessa Venturi;Katherine Kedzierska;Andrew R Lloyd;Rowena A Bull;Fabio Luciani - Immunology and cell biology (2016)
- Communication in Neural Circuits: Tools, Opportunities, and Challenges. - Talia N Lerner;Li Ye;Karl Deisseroth - Cell (2016)
- Ribosome Footprint Profiling of Translation throughout the Genome. - Nicholas T Ingolia - Cell (2016)
- The potential of single-cell profiling in plants. - Idan Efroni;Kenneth D Birnbaum - Genome biology (2016)
- Design and computational analysis of single-cell RNA-sequencing experiments. - Rhonda Bacher;Christina Kendziorski - Genome biology (2016)
- Single-cell sequencing in stem cell biology. - Lu Wen;Fuchou Tang - Genome biology (2016)
- Potentials of single-cell biology in identification and validation of disease biomarkers. - Furong Niu;Diane C Wang;Jiapei Lu;Wei Wu;Xiangdong Wang - Journal of cellular and molecular medicine (2016)
- CEL-Seq2: sensitive highly-multiplexed single-cell RNA-Seq. - Tamar Hashimshony;Naftalie Senderovich;Gal Avital;Agnes Klochendler;Yaron de Leeuw;Leon Anavy;Dave Gennert;Shuqiang Li;Kenneth J Livak;Orit Rozenblatt-Rosen;Yuval Dor;Aviv Regev;Itai Yanai - Genome biology (2016)
... (252 more literatures)
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