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  2. Single-cell sequencing - Wikipedia

    en.wikipedia.org/wiki/Single-cell_sequencing

    Single-cell DNA genome sequencing involves isolating a single cell, amplifying the whole genome or region of interest, constructing sequencing libraries, and then applying next-generation DNA sequencing (for example Illumina, Ion Torrent). Single-cell DNA sequencing has been widely applied in mammalian systems to study normal physiology and ...

  3. List of RNA-Seq bioinformatics tools - Wikipedia

    en.wikipedia.org/wiki/List_of_RNA-Seq...

    SCell [124] integrated analysis of single-cell RNA-seq data. Seurat [125] [126] R package designed for QC, analysis, and exploration of single-cell RNA-seq data. Sincell [127] an R/Bioconductor package for statistical assessment of cell-state hierarchies from single-cell RNA-seq. SINCERA [128] A Pipeline for Single-Cell RNA-Seq Profiling Analysis.

  4. 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 ...

  5. Single cell epigenomics - Wikipedia

    en.wikipedia.org/wiki/Single_cell_epigenomics

    Single cell ATAC-seq has been performed since 2015, using methods ranging from FACS sorting, microfluidic isolation of single cells, to combinatorial indexing. [8] In initial studies, the method was able to reliably separate cells based on their cell types, uncover sources of cell-to-cell variability, and show a link between chromatin ...

  6. RNA-Seq - Wikipedia

    en.wikipedia.org/wiki/RNA-Seq

    Single-cell RNA sequencing (scRNA-Seq) provides the expression profiles of individual cells. Although it is not possible to obtain complete information on every RNA expressed by each cell, due to the small amount of material available, patterns of gene expression can be identified through gene clustering analyses .

  7. 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]

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  9. Single-molecule real-time sequencing - Wikipedia

    en.wikipedia.org/wiki/Single-molecule_real-time...

    The DNA sequencing is done on a chip that contains many ZMWs. Inside each ZMW, a single active DNA polymerase with a single molecule of single stranded DNA template is immobilized to the bottom through which light can penetrate and create a visualization chamber that allows monitoring of the activity of the DNA polymerase at a single molecule level.

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