Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

BSmooth.tstat error, Error in compute.correction #108

Open
yang-mj opened this issue Mar 23, 2022 · 5 comments
Open

BSmooth.tstat error, Error in compute.correction #108

yang-mj opened this issue Mar 23, 2022 · 5 comments

Comments

@yang-mj
Copy link

yang-mj commented Mar 23, 2022

I am trying to run the BSmooth.tstat command for 45 treatment cases and 35 control samples. When I used qSD=0.75 and local.correct=TRUE paramters on the smoothed data , I got the following error:
error in evaluating the argument 'args' in selecting a method for function 'do.call': NA/NaN/Inf in foreign function call (arg 2)

while BSmooth.tstat completed successfully when I used a qSD value <= 0.65 or >=0.85 and local.correct=TRUE

Is there any suggestion for choosing qSD and why it failed when I used the default qSD value?

Thank you!

sessionInfo()
R version 4.1.2 (2021-11-01)
Platform: x86_64-conda-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)

Matrix products: default
BLAS/LAPACK: $HOME/anaconda2/envs/r_412/lib/libopenblasp-r0.3.18.so

locale:
[1] C

attached base packages:
[1] parallel  stats4    stats     graphics  grDevices utils     datasets
[8] methods   base

other attached packages:
 [1] locfit_1.5-9.5              bsseq_1.30.0
 [3] SummarizedExperiment_1.24.0 Biobase_2.54.0
 [5] MatrixGenerics_1.6.0        matrixStats_0.61.0
 [7] GenomicRanges_1.46.1        GenomeInfoDb_1.30.1
 [9] IRanges_2.28.0              S4Vectors_0.32.3
[11] BiocGenerics_0.40.0

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.8                restfulr_0.0.13
 [3] compiler_4.1.2            XVector_0.34.0
 [5] R.methodsS3_1.8.1         R.utils_2.11.0
 [7] rhdf5filters_1.6.0        bitops_1.0-7
 [9] tools_4.1.2               DelayedMatrixStats_1.16.0
[11] zlibbioc_1.40.0           BSgenome_1.62.0
[13] lifecycle_1.0.1           rhdf5_2.38.0
[15] lattice_0.20-45           rlang_1.0.2
[17] Matrix_1.4-0              DelayedArray_0.20.0
[19] cli_3.2.0                 yaml_2.3.5
[21] GenomeInfoDbData_1.2.7    rtracklayer_1.54.0
[23] Biostrings_2.62.0         gtools_3.9.2
[25] grid_4.1.2                data.table_1.14.2
[27] R6_2.5.1                  HDF5Array_1.22.1
[29] XML_3.99-0.8              BiocParallel_1.28.3
[31] limma_3.50.1              Rhdf5lib_1.16.0
[33] GenomicAlignments_1.30.0  Rsamtools_2.10.0
[35] scales_1.1.1              sparseMatrixStats_1.6.0
[37] permute_0.9-7             colorspace_2.0-3
[39] RCurl_1.98-1.6            munsell_0.5.0
[41] rjson_0.2.21              crayon_1.5.0
[43] R.oo_1.24.0               BiocIO_1.4.0
@PeteHaitch
Copy link
Contributor

Hi @yang-mj,

I'm not sure why that it wouldn't be working for the default value of qSd but is for others values both less-than or more-than the default.
It's not a parameter I have much experience with, but perhaps @kasperdanielhansen may be able to provide some ideas.

Cheers,
Pete

@kasperdanielhansen
Copy link
Contributor

kasperdanielhansen commented Apr 2, 2022 via email

@priyatamapandey
Copy link

Hi All,
I am having the same issue while running the tstats. It fails while computing across the sample. I have also tired with estimate.var = "same" but retuned the same error.

@yang-mj, any suggestion whether you were able to fix it?

Screenshot 2023-04-27 at 10 54 23 AM

Thank you,
Priya

@yang-mj
Copy link
Author

yang-mj commented Apr 27, 2023

@priyatamapandey I fixed it by swapping these two groups. What I did was only used symmetric CpG sites with minimum 10x coverage (http://smithlabresearch.org/software/methpipe/) and then followed the bsseq pipeline on bsseq's website. So try to set D1 D2 as either group1 or group2 and it'll probably be fixed

@priyatamapandey
Copy link

Thank you for your quick reply. I swapped the group as group2 = c("D1","D2") and kept estimate.var = "group2". It did not fail but Is it statistically correct?
As in the base documentation it says that two groups being compared (it is always group1 - group2 ) and estimate.var is considers based on the low variability samples.

I am attaching the plot while looking the plot what cutoff to choose and put in dmrFinder function further, any suggestion is appreciated?
Screenshot 2023-04-27 at 2 31 46 PM

Thank you,
Priya

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

4 participants