10X Genomics Resources
If you are new to 10x single cell sequencing or need to brush-up on your knowledge, the 10x “University” found at, https://www.10xgenomics.com/10x-university/, is a great place to start. Here you will find a wealth of training videos, seminars etc. We highly recommend that you watch the videos, relevant for your experiment, before planning any 10x experiments and/or going in the lab:
Training modules:
Single Cell Gene Expression Chapter 1-10.
Single Cell Immune Profiling Chapter 1-8.
- Chapter 4 about cell preparation is very important!
How-to Videos (Lab videos)
Single Cell Gene Expression Chapter 1-11.
Single Cell Immune Profiling Chapter 1-11.
Cell number and Sequencing depth
Cell number calculator:
https://satijalab.org/howmanycells
Resolving PBMC cell types as a function of read depth and cell number: https://support.10xgenomics.com/single-cell-gene-expression/sequencing/doc/technical-note-resolving-cell-types-as-a-function-of-read-depth-and-cell-number
Additional resources about sequencing depth/saturation:
https://kb.10xgenomics.com/hc/en-us/articles/115005062366-What-is-sequencing-saturation-
Resolving T-cell antigen specificity by using 10x compatible dextramers
dCODE MHC dextramers from immudex in combination with 10x VDJ-scRNAseq can be used to resolve the antigen specificity of single T-cells, read more here:
https://www.immudex.com/products/dcode-fbc-10x.aspx
Cell surface protein expression measurement using barcoded antibodies
10x feature barcoding technology allows for measuring cell surface protein expression by using antibodies conjugated with a DNA barcodes. 10x compatible antibodies and workflows are available from biolegend.
https://www.biolegend.com/en-us/totalseq
Cell Hashing for sample multiplexing and duplicate discrimination
Tagging cells with DNA barcoded antibodies targeting ubiquitous cell-surface markers allows for sample multiplexing and “super-loading” (10.000 vs 20.000 recovered cells/lane) of the individual lanes in the 10x chip, effectively decreasing the cost of the experiment. In addition, cell hashing helps identify droplets with more than one cell in it during analysis. It should be noted that super-loading is not supported by 10x Genomics. Read more here:
https://www.biolegend.com/en-us/totalseq
https://genomebiology.biomedcentral.com/articles/10.1186/s13059-018-1603-1