Single cell Omics

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Introduction

  • Part of the standard repertoire of biological research techniques
  • Look at heterogeneity
  • avoids caveat of bulk averaging
  • heterogenous tissue
  • cell number
  • developmental stages
  • allows inference of dynamic processes
  • multiple asynchronous states of a cell states
  • transcriptional profile that happens across those time stages
  • interrogate potential mechanisms at cellular resolution

Sample Prep

  1. Solid tissue
  2. dissociation
  3. single cell isolation
  4. generate cdna library
  5. amplify cdna productcuts ususlally PCR
  • droplet-based gel cell barcode
  • plate-based sc-Seq using flow cytometry - allows gating to target cells of interest
    • full length transcript allows get isoform analysis
  • 10xgenomics prep guidelines
    • single cell atac-seq important to. start with their protocols and buffers
  • Try for 90% viability threshold
  • minimize dead cells nucleic acids inhibitors of reverse transcription
  • Miltenyi dead cell removal
  • single NUCLEI sequencing - option for difficult to dissociate tissue, strongly-adherent, fragile cells like neurons, or solid frozen samples
    • More agnostic to variability of selection bias
    • But lower RNA content
    • higher introns retained


Add-on Modalities

  • VDJ sequencing solution from 10x genomics
    • TCR-VCR sequencing
    • TCR clonotypes grouped by t-SNE
  • Antibody feature barcoding
    • cell surface protein coding
    • similar to FACS
    • limited to surface proteins, can't get at transcription factors with this technique
  • Sample multiplexing
    • same as tagging sample subtypes, but have different barcoding
    • can associate which original sample they came from
    • run all the samples together in the sequencing run, reduces technical variation for biological replicates, more statistical power

Analysis Toolkits

==Public datasets==* 10x genomics datasets