| 181 | | This step is relevant for projects that include cells at different stages of a developmental process or other change that is associated with a time course. Specific methods/algorithms for dimensional reduction are available to do this, but they often give very different results. Most of the methods have some concept of pseudotime, metric that one expects is correlated with actual time, but given that they aren't identical, interpretation needs to be performed with caution. |
| | 181 | This step is relevant for projects that include cells at different stages of a developmental process or other change that is associated with a time course. Specific methods/algorithms for dimensional reduction are available to do this. Most of the methods have some concept of pseudotime, metric that one expects is correlated with actual time, but given that they aren't identical, interpretation needs to be performed with caution. |
| | 182 | Diffusion maps work well for this step and they have been implemented in R (https://bioconductor.org/packages/release/bioc/html/destiny.html) and python (https://scanpy.readthedocs.io/en/stable/api/scanpy.tl.diffmap.html). |
