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In statistics, several tools are used to interpret the data. Measures of central tendency represent the characteristics of the data, such as mean, median, and mode. Additionally, measures of variance like standard deviation and range are used to find the spread of data from the mean. Relative standing measures the distance between data locations. Commonly used measures of relative standings are percentile, z score, and quartiles.
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Data are individual items of information obtained from a population or sample. Data may be classified as qualitative (categorical), quantitative continuous, or quantitative discrete. Because it is not practical to measure the entire population in a study, researchers use samples to represent the population. A random sample is a representative group from the population chosen by using a method that gives each individual in the population an equal chance of being included in the sample. Random...
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Counting Proteins in Single Cells with Addressable Droplet Microarrays
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Single-Cell Protein Assays: A Review.

Beiyuan Fan1,2, Junbo Wang3,4, Ying Xu5

  • 1State Key Laboratory of Transducer Technology, Institute of Electronics, Chinese Academy of Sciences, Beijing, 100190, China.

Methods in Molecular Biology (Clifton, N.J.)
|March 15, 2018
PubMed
Summary

Single-cell proteomics quantifies protein levels in individual cells, revealing cellular differences. Emerging techniques offer new ways to measure protein copy numbers, advancing our understanding of cell heterogeneity.

Keywords:
Droplet cytometryFlow cytometryMass cytometryMicroengravingSingle-cell barcoding microchipSingle-cell protein assays

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Area of Science:

  • Proteomics
  • Cell Biology
  • Biotechnology

Background:

  • Cellular heterogeneity is crucial for understanding biological processes.
  • Single-cell analysis provides deeper insights than bulk analysis.
  • Quantifying protein levels at the single-cell level is a growing area of research.

Purpose of the Study:

  • To review emerging techniques for single-cell protein quantification.
  • To compare the advantages and limitations of various methods.
  • To highlight future research directions in single-cell proteomics.

Main Methods:

  • Flow cytometry
  • Mass cytometry
  • Droplet cytometry
  • Microengraving
  • Single-cell barcoding microchip

Main Results:

  • Each technique offers unique capabilities for protein copy number measurement.
  • Comparison reveals trade-offs in sensitivity, throughput, and multiplexing.
  • Emerging methods show promise for overcoming current limitations.

Conclusions:

  • Single-cell proteomics is essential for dissecting cellular heterogeneity.
  • A variety of techniques are available, each with specific applications.
  • Continued development of these methods will drive future discoveries.