search

lgatto / 2017-spatialmap-robin

Robin's 'Spatial Proteomics Data Dissemination' project
1 stars 0 forks source link

t-SNE evaluation #3

Open lgatto opened 7 years ago

lgatto commented 7 years ago

To set reasonable parameters for the t-SNE visualisation in the online app, we need to assess the hyper-paramters on all (or many) dataset. An example of how to do this is shown in the vignette. In a nutshell, one needs to iterate over a range of steps and perplexity values and produce the grid of PCA plots.

@Kohze - could you create an Rmd file with this analysis in sci-reports/rsne.Rmd and update this issue once it is ready. Thanks!

Kohze commented 7 years ago

Did a first test run on 5 Datasets and will run over some night the next days the same procedure over all datasets (or directly on a server).

The TSNE: The perplexity fixed to 35 and the iterations indicated on top of each plot. tsne

As comparrison the PCA of the same data. pcacomp

lgatto commented 7 years ago

It is important in such cases to be systematic. Best approach would be to do this analysis for each dataset separately, and for a range of perplexities and steps, as the number of step to converge will depend on the perplexity itself.