dynverse / dynmethods

A collection of 50+ trajectory inference methods within a common interface 📥📤
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infer_trajectory() does not produce any output #167

Open lemdcock opened 3 years ago

lemdcock commented 3 years ago

Dear Dynmethods team,

I'm working with single cell data and as part of our data analysis we would like to perform trajectory inference. Since dynverse offers a wide range of TI methods, I was very excited to try this. However, I've run into some trouble with the infer_trajectory() function. When docker is running it appears to download the correct image and afterwards attempts to run it. At this point lies my problem as the function appears to run a few seconds after which I get a prompt, but no output. Since I'm working with an Apple Silicon based MacBook Pro, I thought the architecture of the chip was causing the issue. However, when I tried the same code on an Intel based MacBook Pro, I had the same issue.

I've run test_docker_installation on both Macs and this is the output: ✔ Docker is installed ✔ Docker daemon is running ✔ Docker is at correct version (>1.0): 1.41 ✔ Docker is in linux mode ✔ Docker can pull images ✔ Docker can run image ✔ Docker can mount temporary volumes ✔ Docker test successful ----------------------------------------------------------------- [1] TRUE

My docker installation thus appears to be fine. I then thought my data might be the problem and thus downloaded the example data provided by dynverse. However, infer_trajectory() failed here as well. Am I doing something wrong? What can I do to fix this?

Kind regards, Laurenz De Cock

Code for example dataset:

Dynverse Example Dataset

Load Required Libraries

library(Seurat) library(ggplot2) library(dynmethods) library(dynwrap) library(Matrix) library(tidyr)

Load Example Dataset

example_dataset <- dynwrap::example_dataset

Prepare Data

dataset <- wrap_expression( expression = example_dataset$expression, counts = example_dataset$counts )

dataset <- add_prior_information( dataset, start_id = "Cell1" )

dataset <- add_dimred( dataset, example_dataset$dimred )

Run trajectory inference

model <- infer_trajectory(dataset, ti_comp1())