eblancoga / spikChIP

spikChIP is a computational pipeline to perform multiple alternative normalization corrections on ChIP-seq data with spike-in (Raw, Traditional, ChIP-Rx, Tag removal and spikChIP)
GNU General Public License v3.0
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normalize.loess error #5

Open rlbc opened 5 months ago

rlbc commented 5 months ago

Hi,

Thank you for developing such a useful tool. I'm currently attempting to use spikChIP with human cell line samples and have encountered an error while running the R script (avg.R). The error message is:

mn <- normalize.loess(m,subset=s)
Error in simpleLoess(y, x, w, span, degree = degree, parametric = parametric,  : 
  NA/NaN/Inf in foreign function call (arg 1)
In addition: There were 44 warnings (use warnings() to see them)

All values within the script are greater than 0.1, and there are no NAs, at least.

Here is my R session:

sessionInfo()
R version 4.0.3 (2020-10-10)
Platform: x86_64-conda-linux-gnu (64-bit)
Running under: Ubuntu 20.04.6 LTS

Matrix products: default

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

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

other attached packages:
[1] MASS_7.3-60.0.1     affy_1.68.0         Biobase_2.50.0     
[4] BiocGenerics_0.36.1

loaded via a namespace (and not attached):
[1] BiocManager_1.30.22   zlibbioc_1.36.0       compiler_4.0.3       
[4] affyio_1.60.0         preprocessCore_1.52.1

Could you provide some guidance on resolving this issue? I appreciate your help.

Thanks

eblancoga commented 5 months ago

Hi Rafael,

Sure, I've seen sometimes this bug due to very low number of spike-in reads (or null) in the samples. What proportion/totals of human vs spike-in genome reads do you see in your BAM files?

Best,

Enrique


Dr. Enrique Blanco García (PhD)

https://sites.google.com/site/eblancog2014/

http://orcid.org/0000-0001-6261-7370

Epigenetic Events in Cancer (L. Di Croce's lab) Gene Regulation, Stem Cells and Cancer Centre for Genomic Regulation (CRG)

C/ Dr. Aiguader, 88

08003 Barcelona

Spain


De: Rafael @.> Enviado: martes, 16 de abril de 2024 10:28 Para: eblancoga/spikChIP @.> Cc: Subscribed @.***> Asunto: [eblancoga/spikChIP] normalize.loess error (Issue #5)

Hi,

Thank you for developing such a useful tool. I'm currently attempting to use spikChIP with human cell line samples and have encountered an error while running the R script (avg.R). The error message is:

mn <- normalize.loess(m,subset=s) Error in simpleLoess(y, x, w, span, degree = degree, parametric = parametric, : NA/NaN/Inf in foreign function call (arg 1) In addition: There were 44 warnings (use warnings() to see them)

I have verified that all values within the script are greater than 0.1 and there are no NAs.

Here is my R session:

sessionInfo() R version 4.0.3 (2020-10-10) Platform: x86_64-conda-linux-gnu (64-bit) Running under: Ubuntu 20.04.6 LTS

Matrix products: default

locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 [7] LC_PAPER=en_US.UTF-8 LC_NAME=C [9] LC_ADDRESS=C LC_TELEPHONE=C [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

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

other attached packages: [1] MASS_7.3-60.0.1 affy_1.68.0 Biobase_2.50.0 [4] BiocGenerics_0.36.1

loaded via a namespace (and not attached): [1] BiocManager_1.30.22 zlibbioc_1.36.0 compiler_4.0.3 [4] affyio_1.60.0 preprocessCore_1.52.1

Could you provide some guidance on resolving this issue? I appreciate your help.

Thanks

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rlbc commented 4 months ago

Hi Enrique,

I'm currently testing the normalization on a few samples. Below are the numbers directly taken from the spikChIP output:

Sample Sample_reads Spike-in_reads
Sample1_RepA 70.887.114 911.670
Sample1_RepB 72.079.319 456.923
Sample2_RepA 82.260.435 980.884
Sample2_RepB 65.073.540 447.052
Sample3_RepA 81.405.013 551.496
Sample3_RepB 62.578.840 283.812
Sample4_RepA 86.845.303 887.901
Sample4_RepB 48.869.587 514.447

Thanks for the help!

Best