Comments (7)
Hi, following up to see if you guys had any suggestions to resolve this error. Thanks
from scavenge.
Hi, sorry for the late reply! I have no idea about this error, can you post more information about your data and output? Thank you!
from scavenge.
Hi, I used ~3000 fine-mapped SNPs as input and here is the RSE object with peak count matrix. TRS gets calculated successfully but not the permutation step. I see that there is a discrepancy in the no. of cells - 200071 is original rse but np_score was calculated only for 199779 cells. Could this be the issue? but seems unlikely becuase permutation step does not use original rse. please let me know if you would like to look at a specific output from the pipeline. Thank you!
class: RangedSummarizedExperiment
dim: 6 200071
metadata(0):
assays(1): counts
rownames: NULL
rowData names(2): bias idx
colnames(200071): atac_A1B1#CACCACTTCCAGGTAT-1
atac_A1B1#GTAGGAGTCCGGGCAT-1 ... atac_A28B28#TGCTATTAGAGTGGTC-1
atac_A28B28#CCTTGCATCGCAAGCC-1
colData names(123): orig.ident nCount_peaks ... nCount_RNA nFeature_RNA
from scavenge.
Thank you for the info.
I figure the discrepancy is not the cause of this error if your input for the dimension of knn_sparse_mat
and length of topseed_npscore
matched. I noticed that in your previous error there is a number of 199764 that should be the number related to the permutation output, which is different than the number of your input 199779. I think this could be the key. Can you post the entire error message of this analysis? thank you!
from scavenge.
1000
Stationary step: 80
Stationary Delta: 9.63450666772587e-06
Stationary step: 81
Stationary Delta: 9.48843841608067e-06
Stationary step: 74
Stationary Delta: 9.99591098634589e-06
Stationary step: 74
Stationary Delta: 9.44719369263237e-06
Stationary step: 74
Stationary Delta: 9.4838064933629e-06
Stationary step: 75
Stationary Delta: 9.79173786751816e-06
Error in (function (..., row.names = NULL, check.rows = FALSE, check.names = TRUE, :
arguments imply differing number of rows: 0, 199845
Calls: get_sigcell_simple ... as.data.frame -> as.data.frame.list -> do.call ->
In addition: Warning message:
In mclapply(1:permutation_times, mc.cores = mycores, function(i) { :
scheduled cores 1, 2, 3 did not deliver results, all values of the jobs will be affected
Execution halted
slurmstepd: error: Detected 3 oom-kill event(s) in StepId=1237064.batch. Some of your processes may have been killed by the cgroup out-of-memory handler.
from scavenge.
It seems that a out-of-memory issue, can you increase the memory of each core or use one core to process? Also, can you post how it goes with just 100 times permutation for 1 core and 4 cores, respectively?
from scavenge.
Hi, this was resolved with 5 cores and more memory!
Thanks
from scavenge.
Related Issues (9)
- Potential for scRNA-seq? HOT 1
- Missing wiki page HOT 2
- Two analyses of the same code yielded different results HOT 1
- Fine mapping to reproduce COVID19 results HOT 2
- Recommended R Version and chromVAR installation issues HOT 7
- How to make trait_file from GWAS summary statistics ? HOT 7
- TF-IDF issue HOT 2
- Input issues HOT 1
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from scavenge.