Trajecoty can't be reconstructed because of distortions introduced by UMAP

Nobody has claimed this yet.

Hi,

I have a developing mouse brain dataset of 20,000 cells.When I performed downstream analyses with a different number of PCs (Fig1), the UMAP results differ dramatically.

As you see from Fig1, if I choose 3-4 PCs, two populations of IPC (IPC1 and IPC2) flock together and connect with RGC. The best result is 5 PCs, IPC2 and IPC1 are separated and close to RGC, which is in line with our expectation. Since UMAP better resolves the global and continuous structure of the differentiation manifold, it is used for visualizing the developmental trajectories of cells. In this UMAP representation,we can see a trajectory of great biological significance :RGC>IPC1 and IPC2>Neuron.

But in Seurat tutorial, it referred that performing downstream analyses with only 5 PCs does signifcanltly and adversely affect results. It's obvious that 5 PCs is not enough for explaining the variance of 20,000 cells. Both JackStrawPlot and ElbowPlot also showed that 40-50 PCs may be an appropriate choice for our dataset.

However, if I choose more than 5 PCs, IPC2 somehow jumps out and keeps away from IPC1 and RGC. This really puzzled me, because a trajectory can not be RGC>IPC1>Neuron>IPC2 as it is shown in Fig3. And one reviewer for our paper also raised this question and doubted that the mapping of the IPC2 cluster is somewhat flawed. But I indeed followed the guided tutorial and repeated this procedure many times, only to get similar result. If the IPC2 cluster can't link to RGC cell in umap, how can Monocle3 recognize the lineage relationship between them and reconstruct the trajectory?

I really don't know how to explain this. The only explanation I can think of is distortions introduced by UMAP. See[ this paper](https://www.biorxiv.org/content/10.1101/689851v3) for the extent non-linear dimension reduction methods distort the data.

Do you have any advice on my analysis or reply to reviewers? I will be much appreciated if you can hep me with it.

Sophia

Start by comparing the 3–5-PC and 40–50-PC UMAP results described in the issue and read the linked paper on nonlinear dimensional-reduction distortion. A useful resolution would explain whether the observed IPC/RGC separation is expected UMAP behavior and how it affects interpreting the Monocle3 trajectory.

Written by the indexing model from the issue text.