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"Killed singularity $*" error running new.prism() #3
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Thank you for your interest in our work. Here are the answers to your
questions:
1.
For my single cell data only cell types information is available. I am
not sure how to subtype these cells to come up with the cell states. For
now I am using the cell types as both cell.type.labels and
cell.state.labels as it is mandatory to provide both. Let me know if it is
ok.
Yes. If you do not have cell states, you can certainly define them using
the cell state label.
I noticed that you have used the argument key="NULL", which should be
key=NULL. I guess it was a typo, as otherwise new.prism will throw an error.
2.
The initial data preparation went very well for my data. I just
converted the single cell data sparse matrix to dense matrix and I selected
only protein coding genes for Prism construction.
It looks like your memory is exhausted. Try remove all variables other
than myPrism from your R environment and then clean up the memory using
gc(). You may also try reducing the number of threads.
Best,
Tinyi
…On Tue, Jun 28, 2022 at 1:50 AM monalisa6hota ***@***.***> wrote:
Hello!
I am trying to run BayesPrism for my bulk RNAseq data sample size ~200 and
Single cell data, no of cells ~70000. I am working with non-malignant
samples. Here is the issue I am facing. Please let me know how to solve
this.
1.
For my single cell data only cell types information is available. I am
not sure how to subtype these cells to come up with the cell states. For
now I am using the cell types as both cell.type.labels and
cell.state.labels as it is mandatory to provide both. Let me know if it is
ok.
2.
The initial data preparation went very well for my data. I just
converted the single cell data sparse matrix to dense matrix and I selected
only protein coding genes for Prism construction.
*My code is here:*
myPrism <- new.prism(
reference=sc.dat.filtered.pc,
mixture=bk.dat,
input.type="count.matrix",
cell.type.labels = cell.type.labels,
cell.state.labels = cell.type.labels,
key="NULL",
outlier.cut=0.01,
outlier.fraction=0.1,
)
I am running this job in a cluster with 120GB memory. The job runs for few
minutes, provides the cell state information and then terminates with this
error
*I am getting following error*
#> number of cells in each cell state
#> cell.state.labels
#> PJ017-tumor-6 PJ032-tumor-5 myeloid_8 PJ032-tumor-4
#> 22 41 49
/sw/Containers/singularity/bin/run_singularity: line 28: 42360 Killed
singularity $*
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Thank you so much Tinyi for such quick response. You were right, my memory was exhausted. I tried to run it with 500GB memory, it worked fine. |
tinyi
added a commit
that referenced
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Nov 4, 2022
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Hello!
I am trying to run BayesPrism for my bulk RNAseq data sample size ~200 and Single cell data, no of cells ~70000. I am working with non-malignant samples. Here is the issue I am facing. Please let me know how to solve this.
For my single cell data only cell types information is available. I am not sure how to subtype these cells to come up with the cell states. For now I am using the cell types as both cell.type.labels and cell.state.labels as it is mandatory to provide both. Let me know if it is ok.
The initial data preparation went very well for my data. I just converted the single cell data sparse matrix to dense matrix and I selected only protein coding genes for Prism construction.
My code is here:
myPrism <- new.prism(
reference=sc.dat.filtered.pc,
mixture=bk.dat,
input.type="count.matrix",
cell.type.labels = cell.type.labels,
cell.state.labels = cell.type.labels,
key="NULL",
outlier.cut=0.01,
outlier.fraction=0.1,
)
#I am running this job in a cluster with 120GB memory. This job runs for few minutes, provides the cell state information and terminates with this error.
I am getting following error
#> number of cells in each cell state
#> cell.state.labels
#> PJ017-tumor-6 PJ032-tumor-5 myeloid_8 PJ032-tumor-4
#> 22 41 49
/sw/Containers/singularity/bin/run_singularity: line 28: 42360 Killed singularity $*
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