Concatenation, tSNE, and Clustering with Tim Quinn Crawford, PhD 5/17/18 скачать в хорошем качестве

Concatenation, tSNE, and Clustering with Tim Quinn Crawford, PhD 5/17/18

tSNE is a dimensionality reduction tool designed for assisting in the analysis of data sets with large numbers of parameters. tSNE produces two new parameters that effectively summarize all of the information contained in all other parameters. To compare different samples using tSNE, you must first concatenated (merge) the individual samples you wish to compare, then run tSNE on the concatenated file to produce a common dimensionally reduced data space. You can then use gating to pull apart the concatenated file into individual samples and compare how each of those samples is represented in the dimensionally reduced data space. To discover phenotypic changes or shifts between experimental conditions, gate the distinct populations you see in the common tSNE plot, use the original parameters to immunophenotype the populations and then compare the prevalence of those populations of between experimental conditions.