Difference between revisions of "Single cell Omics"
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| − | ==Introduction== | + | ==Mike Kelly talk== |
| + | ===Introduction=== | ||
* Part of the standard repertoire of biological research techniques | * Part of the standard repertoire of biological research techniques | ||
* Look at heterogeneity | * Look at heterogeneity | ||
| Line 11: | Line 12: | ||
* interrogate potential mechanisms at cellular resolution | * interrogate potential mechanisms at cellular resolution | ||
| − | ==Sample Prep== | + | ===Sample Prep=== |
# Solid tissue | # Solid tissue | ||
# dissociation | # dissociation | ||
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* droplet-based gel cell barcode | * droplet-based gel cell barcode | ||
* plate-based sc-Seq using flow cytometry - allows gating to target cells of interest | * plate-based sc-Seq using flow cytometry - allows gating to target cells of interest | ||
| + | * What is the RNA quality? We don't know. Fixed cells? time since extraction can have a big affect on data quality | ||
** full length transcript allows get isoform analysis | ** full length transcript allows get isoform analysis | ||
* 10xgenomics prep guidelines | * 10xgenomics prep guidelines | ||
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** run all the samples together in the sequencing run, reduces technical variation for biological replicates, more statistical power | ** run all the samples together in the sequencing run, reduces technical variation for biological replicates, more statistical power | ||
| − | ==Analysis Toolkits== | + | ===Analysis Toolkits=== |
* Loupe Cell Browser (free from 10x genomics) | * Loupe Cell Browser (free from 10x genomics) | ||
* Partek flow (14-day free trial) | * Partek flow (14-day free trial) | ||
| Line 53: | Line 55: | ||
* [https://nih-irp-singlecell.github.io NIH Single Cell Community] | * [https://nih-irp-singlecell.github.io NIH Single Cell Community] | ||
| − | ==Public datasets== | + | ===Public datasets=== |
* [https://www.10xgenomics.com/resources/datasets/ 10x genomics datasets] | * [https://www.10xgenomics.com/resources/datasets/ 10x genomics datasets] | ||
| + | |||
| + | ==Nan Ping talk== | ||
| + | * innate immunity - non specific | ||
| + | * adaptive immunity - b cells antibody, CD4 hemper cells and CD8 killer cells | ||
| + | * functional decline in age | ||
| + | * naive t cells - then expansion and proliferation into effector cells, becomes memory cells. 7 different types of t-cells known | ||
| + | * What type of lymphocyes are reduced by age - naive | ||
| + | * how many CD8 sub populations are there? | ||
| + | * Age increase in number of cells, or expression level within a cell, or both? | ||
Revision as of 14:00, 23 May 2019
Contents
Mike Kelly talk
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
- What is the RNA quality? We don't know. Fixed cells? time since extraction can have a big affect on data quality
- 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
- Seurat - R toolkit for single cell genomics
- t-SNE presentation on statquest
- NIH Single Cell Community
Public datasets
Nan Ping talk
- innate immunity - non specific
- adaptive immunity - b cells antibody, CD4 hemper cells and CD8 killer cells
- functional decline in age
- naive t cells - then expansion and proliferation into effector cells, becomes memory cells. 7 different types of t-cells known
- What type of lymphocyes are reduced by age - naive
- how many CD8 sub populations are there?
- Age increase in number of cells, or expression level within a cell, or both?
