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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. CITE-Seq - Wikipedia

    en.wikipedia.org/wiki/CITE-Seq

    Analysis of single-cell sequencing presents many challenges, such as determining the best way to normalize the data. [8] Due to a new level of complications that arise from sequencing of both proteins and transcripts at a single-cell level, the developers of CITE-Seq and their collaborators are maintaining several tools to help with data analysis.

  4. 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.

  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. Tcr-seq - Wikipedia

    en.wikipedia.org/wiki/Tcr-seq

    TCR-Seq (T-cell Receptor Sequencing) is a method used to identify and track specific T cells and their clones. [1] TCR-Seq utilizes the unique nature of a T-cell receptor (TCR) as a ready-made molecular barcode. [1] This technology can apply to both single cell sequencing technologies and high throughput screens [1]

  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]

  8. Single cell epigenomics - Wikipedia

    en.wikipedia.org/wiki/Single_cell_epigenomics

    Each method is labelled on the bottom row. Arrows are coloured by method, showing the flow from starting material to sequence data. Adapted from [1] Single cell epigenomics is the study of epigenomics (the complete set of epigenetic modifications on the genetic material of a cell) in individual cells by single cell sequencing.

  9. File:Single Cell Genome Sequencing Workflow.pdf - Wikipedia

    en.wikipedia.org/wiki/File:Single_Cell_Genome...

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