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infer_trajectory() does not produce any output #167

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lemdcock opened this issue Aug 25, 2021 · 0 comments
Open

infer_trajectory() does not produce any output #167

lemdcock opened this issue Aug 25, 2021 · 0 comments

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@lemdcock
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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())

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