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  2. Single-cell transcriptomics - Wikipedia

    en.wikipedia.org/wiki/Single-cell_transcriptomics

    RNA Seq Experiment. The single-cell RNA-seq technique converts a population of RNAs to a library of cDNA fragments. 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]

  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 sequencing - Wikipedia

    en.wikipedia.org/wiki/Single-cell_sequencing

    The single-cell RNA-Seq protocols vary in efficiency of RNA capture, which results in differences in the number of transcripts generated from each single cell. Single-cell libraries are usually sequenced to a depth of 1,000,000 reads because a large majority of genes are detected with 500,000 reads. [ 104 ]

  5. RNA-Seq - Wikipedia

    en.wikipedia.org/wiki/RNA-Seq

    RNA-Seq can also be used to determine exon/intron boundaries and verify or amend previously annotated 5' and 3' gene boundaries. Recent advances in RNA-Seq include single cell sequencing, bulk RNA sequencing, [6] 3' mRNA-sequencing, in situ sequencing of fixed tissue, and native RNA molecule sequencing with single-molecule real-time sequencing. [7]

  6. CITE-Seq - Wikipedia

    en.wikipedia.org/wiki/CITE-Seq

    CITE-Seq (Cellular Indexing of Transcriptomes and Epitopes by Sequencing) is a method for performing RNA sequencing along with gaining quantitative and qualitative information on surface proteins with available antibodies on a single cell level. [1] So far, the method has been demonstrated to work with only a few proteins per cell.

  7. Nvidia Parabricks - Wikipedia

    en.wikipedia.org/wiki/NVIDIA_Parabricks

    Standard pipeline to extract variants from an individual's genome Sequencing machines able to identify the sequence of bases constituting the DNA. The massive reduction in sequencing costs [2] resulted in a significant increase in the size and the availability of genomics data [3] with the potential of revolutionizing many fields, from medicine to drug design.

  8. Transcriptomics technologies - Wikipedia

    en.wikipedia.org/wiki/Transcriptomics_technologies

    UMIs are particularly well-suited to single-cell RNA-Seq transcriptomics, where the amount of input RNA is restricted and extended amplification of the sample is required. [73] [74] [75] Once the transcript molecules have been prepared they can be sequenced in just one direction (single-end) or both directions (paired-end).

  9. Transcriptome - Wikipedia

    en.wikipedia.org/wiki/Transcriptome

    Single-cell RNA sequencing (scRNA-seq) is a recently developed technique that allows the analysis of the transcriptome of single cells, including bacteria. [25] With single-cell transcriptomics, subpopulations of cell types that constitute the tissue of interest are also taken into consideration. [26]

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