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The following is the 2020 Single Cell Research Report From Gene wisdom recommended by recordtrend.com. And this article belongs to the classification: Biological industry, research report.
（1） Key and difficult points of experimental technology
In order to obtain high-quality single cell sequencing, we must fully understand the sample type and optimize the experimental operation according to the specific sample.
If the method is not appropriate, the gene expression profile of cells may change, and even some of the more sensitive cells to the environment will die and release to the surrounding environment after lysis, resulting in background noise in the detection, thus affecting the quality of single cell data. Therefore, it is necessary to avoid cell death and lysis, optimize the preparation conditions, speed up the experimental process and reduce the stimulation to the sample cells. In addition, the development of single cell extraction technology should be considered for cryopreserved human tissue samples and tissue types without ideal single cell suspension.
At present, although the application of microfluidic technology makes the flux of a single cell reach tens of thousands of cells, both droplet microfluidic technology and microporous separation technology need a large number of cell samples, which is not friendly to some rare samples that are difficult to obtain. Moreover, most of the current high-throughput transcriptome platforms can only achieve 3 ‘or 5’ end sequencing, and cannot obtain more abundant full-length transcriptional information. In addition, the total number of genes detected in a single cell is relatively low due to the pico level of DNA and RNA content. Moreover, due to the problem of capture efficiency in the amplification process, there will still be amplification bias. For example, small fragments may have a greater probability of enrichment, which will affect the data analysis.
（2） Single cell sequencing data processing is difficult
Compared with traditional sequencing, single-cell sequencing will produce more background noise data, because the initial amount of DNA or RNA in a single cell is too small, and the tiny deviation between amplification and capture will be amplified after multiple amplification, resulting in huge differences between cells that have nothing to do with biological significance. For example, even highly expressed transcripts may be missed due to capture efficiency, resulting in false negative results. And some genes with low expression may be enriched due to amplification, resulting in data distortion.
Secondly, the batch effect between different samples is also a difficulty in processing single cell data. Batch effect is the natural difference between the samples which are sequenced independently, sometimes it is difficult to distinguish from the real biological difference. If the experimental design is not reasonable, there may be a large batch effect. Moreover, sometimes the differences between cells may be due to cell size, cell cycle status and other factors, which also brings some difficulties to the identification of cell types.
（3） Single cell multi omics analysis is difficult
In addition to the challenge of experimental technology, the analysis of single-cell data is also important and difficult. In the face of massive single-cell sequencing and flow data, how to combine the multi omics information of a single cell with its cell phenotype and function is the difficulty of bioinformatics analysis, which is of great significance for scientific research and clinical application. However, the current joint analysis is generally limited to two or three kinds of omics.
（4） Lack of single cell related professionals
Single cell technology involves core technologies such as microfluidics, very micro quantitative analysis, massive data analysis and so on, which requires high personnel ability. At present, it is mostly used in scientific research, and the degree of industrial transformation is not high. At the same time, compared with the common sequencing technology, the current single cell sequencing cost is high, and it is not suitable for large-scale clinical application. There is an urgent need for R & D talents to reduce costs, optimize processes, develop more tools, and promote transformation and application.
Development and Prospect
（1） Technology development trend: separation efficiency and flux, high-throughput multi omics research
The main trend of single cell technology development in the future is to improve the efficiency and flux of single cell sorting, realize high-throughput multi omics research, and develop more automated single cell technology platforms, which will help to reduce the cost and technical threshold of single cell technology. For the emerging single-cell proteomics and spatiomics, more dimensional proteomics parameter analysis and higher resolution spatiomics research are the development direction of future technology. At the same time, the combination of single-cell multi omics research and 3D tissue anatomy is also an important trend of future technology development.
The interpretation of massive information generated by single-cell technology is a difficult problem at present. The emerging single-cell technologies such as mass spectrometry, flow cytometry and spatial transcriptome data also need new bioinformatics analysis tools. As more and more single-cell maps are analyzed and single-cell databases are constantly enriched, we expect computational biologists to develop more accurate and effective algorithms and software.
（2） The trend of technology transformation in the future
With the development of the past decade, single cell technology has been widely used in the field of scientific research, including many aspects of transformation research, such as tumor immunity, concomitant diagnosis, drug development, vaccine research, etc. these fields are the direction of technology transformation in the future.
（3） Future industrial development trend
The development of single cell technology industry involves the development of upstream reagents, microfluidic devices, microporous chips, high-throughput sequencer, etc. At present, the cost of reagents and equipment for single cell technology is still very high. As more and more companies and scientific research teams join the industry, the cost of reagents and equipment will gradually decrease. At the same time, with the popularization and wide application of technology, the single cell technology service industry in the middle and lower reaches will also flourish.
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