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  2. Spatial transcriptomics - Wikipedia

    en.wikipedia.org/wiki/Spatial_transcriptomics

    Spatial transcriptomics, or spatially resolved transcriptomics, is a method that captures positional context of transcriptional activity within intact tissue. [1] The historical precursor to spatial transcriptomics is in situ hybridization, [2] where the modernized omics terminology refers to the measurement of all the mRNA in a cell rather than select RNA targets.

  3. RNA-Seq - Wikipedia

    en.wikipedia.org/wiki/RNA-Seq

    RNA-Seq (named as an abbreviation of RNA sequencing) is a technique that uses next-generation sequencing to reveal the presence and quantity of RNA molecules in a biological sample, providing a snapshot of gene expression in the sample, also known as transcriptome.

  4. Transcriptomics technologies - Wikipedia

    en.wikipedia.org/wiki/Transcriptomics_technologies

    Currently RNA-Seq relies on copying RNA molecules into cDNA molecules prior to sequencing; therefore, the subsequent platforms are the same for transcriptomic and genomic data. Consequently, the development of DNA sequencing technologies has been a defining feature of RNA-Seq. [ 78 ] [ 80 ] [ 81 ] Direct sequencing of RNA using nanopore ...

  5. Transcriptome - Wikipedia

    en.wikipedia.org/wiki/Transcriptome

    RNA sequencing is a next-generation sequencing technology; as such it requires only a small amount of RNA and no previous knowledge of the genome. [3] It allows for both qualitative and quantitative analysis of RNA transcripts, the former allowing discovery of new transcripts and the latter a measure of relative quantities for transcripts in a ...

  6. Single-cell transcriptomics - Wikipedia

    en.wikipedia.org/wiki/Single-cell_transcriptomics

    These fragments are sequenced by high-throughput next generation sequencing techniques and the reads are mapped back to the reference genome, providing a count of the number of reads associated with each gene. [13] Normalisation of RNA-seq data accounts for cell to cell variation in the efficiencies of the cDNA library formation and sequencing.

  7. Deterministic Barcoding in Tissue for Spatial Omics Sequencing

    en.wikipedia.org/wiki/Deterministic_Barcoding_in...

    Associating the barcodes with each mRNA sequence provides a spatial transcriptomics map of the tissue. While this is not a single-cell methodology, the 10 uM channels capture only 1-2 cells per square, generating near-single-cell resolution. The ADT sequences capture spatial proteomic information that can be compared to the transcriptomic data.

  8. CITE-Seq - Wikipedia

    en.wikipedia.org/wiki/CITE-Seq

    A unique barcode sequence used on the cell hashing antibody can be designed to be different from an antibody barcode present on the ADTs used in CITE-seq. This makes it possible to couple cell hashing with CITE-seq on a single sequencing run. [12] Cell hashing allows super-loading of the scRNA-seq platform, resulting in a lower cost of sequencing.

  9. Massively parallel signature sequencing - Wikipedia

    en.wikipedia.org/wiki/Massively_parallel...

    After several rounds of sequence determination, using hybridization of fluorescent labeled probes, a sequence signature of ~16–20 bp is determined from each bead. Fluorescent imaging captures the signal from all of the beads, while affixed to a 2-dimensional surface, so DNA sequences are determined from all the beads in parallel.