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* [https://www.10xgenomics.com/resources/datasets/ 10x genomics datasets]
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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==
# Solid tissue
# dissociation
# single cell isolation
# generate cdna library
# 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==
* Loupe Cell Browser (free from 10x genomics)
* Partek flow (14-day free trial)
* FloJo SeqGeq
* [https://satijalab.org/seurat/ Seurat] - R toolkit for single cell genomics
* [https://www.youtube.com/watch?v=NEaUSP4YerM t-SNE presentation on statquest]
* [https://nih-irp-singlecell.github.io NIH Single Cell Community]
==Public datasets==* [https://www.10xgenomics.com/resources/datasets/ 10x genomics datasets]
