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  2. Single-cell sequencing - Wikipedia

    en.wikipedia.org/wiki/Single-cell_sequencing

    Single-cell sequencing examines the nucleic acid sequence information from individual cells with optimized next-generation sequencing technologies, providing a higher resolution of cellular differences and a better understanding of the function of an individual cell in the context of its microenvironment. [1]

  3. Single-cell transcriptomics - Wikipedia

    en.wikipedia.org/wiki/Single-cell_transcriptomics

    Detecting differences in gene expression level between two populations is used both single-cell and bulk transcriptomic data. Specialised methods have been designed for single-cell data that considers single cell features such as technical dropouts and shape of the distribution e.g. Bimodal vs. unimodal. [23]

  4. Tcr-seq - Wikipedia

    en.wikipedia.org/wiki/Tcr-seq

    This method can sequence millions of cells in a single experiment. [5] However, one major disadvantage is that bulk sequencing cannot determine which TCR chains pair together, only the frequency within the repertoire. The large amount of TCRs sampled also means that lower abundance TCRs may not be detected [5] Single cell sequencing can ...

  5. Single-cell analysis - Wikipedia

    en.wikipedia.org/wiki/Single-cell_analysis

    This single cell shows the process of the central dogma of molecular biology, which are all steps researchers are interested to quantify (DNA, RNA, and Protein).. In cell biology, single-cell analysis and subcellular analysis [1] refer to the study of genomics, transcriptomics, proteomics, metabolomics, and cellcell interactions at the level of an individual cell, as opposed to more ...

  6. Cellular deconvolution - Wikipedia

    en.wikipedia.org/wiki/Cellular_deconvolution

    Since most high-throughput technologies use bulk samples and measure the aggregated levels of molecular information (e.g. expression levels of genes) for all cells in a sample, the measured values would be an aggregate of the values pertaining to the expression landscape of different cell types. [3]

  7. Single-cell multi-omics integration - Wikipedia

    en.wikipedia.org/wiki/Single-cell_multi-omics...

    Early integration is a method that concatenates (by binding rows and columns) two or more omics datasets into a single data matrix. [19] [20] Some advantages of early integration are that the approach is simple, highly interpretable, and capable of capturing relationships between features from different modalities.

  8. G&T-Seq - Wikipedia

    en.wikipedia.org/wiki/G&T-Seq

    G&T-seq (short for single cell genome and transcriptome sequencing) is a novel form of single cell sequencing technique allowing one to simultaneously obtain both transcriptomic and genomic data from single cells, allowing for direct comparison of gene expression data to its corresponding genomic data in the same cell...

  9. List of single cell omics methods - Wikipedia

    en.wikipedia.org/wiki/List_of_single_cell_omics...

    A list of more than 100 different single cell sequencing (omics) methods have been published. [1] The large majority of methods are paired with short-read sequencing technologies, although some of them are compatible with long read sequencing.