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  2. List of RNA-Seq bioinformatics tools - Wikipedia

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

    scLVM [117] scLVM is a modelling framework for single-cell RNA-seq data that can be used to dissect the observed heterogeneity into different sources, thereby allowing for the correction of confounding sources of variation. scM&T-Seq Parallel single-cell sequencing.

  3. 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]

  4. 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.

  5. 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]

  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 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 ...

  8. Cellular deconvolution - Wikipedia

    en.wikipedia.org/wiki/Cellular_deconvolution

    Most cellular deconvolution algorithms consider an input data in a form of a matrix , which represents some molecular information (e.g. gene expression data or DNA methylation data) measured over a group of samples and marks (e.g. genes or CpG sites).

  9. 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...