CAGEr : problem while filtering the bamFile
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Vivek.b ▴ 100
@vivekb-7661
Last seen 2.2 years ago
Germany

Dear CAGEr team

I have been trying to run CAGEr on my test dataset and having problem in reading in the BAM files to make CAGEset object.

> input = list.files("test",pattern = "test-.*sorted.bam$",full.names = TRUE)
> mycage <- new("CAGEset", genomeName = "BSgenome.Dmelanogaster.UCSC.dm6",
+                 inputFiles = input, inputFilesType = "bam",
+                 sampleLabels = c("test-C", "test-D", "test-E", "test-G"))
> ctss <- getCTSS(mycage,removeFirstG = TRUE,correctSystematicG = TRUE)

Gives me :

Reading in file: test/test-C_sorted.bam...
	-> Filtering out low quality reads...
	-> Removing the first base of the reads if 'G' and not aligned to the genome...
	-> Estimating the frequency of adding a 'G' nucleotide and correcting the systematic bias...
Error in setnames(CTSS, c("chr", "pos", "strand", sample.labels[i])) : 
  Can't assign 4 names to a 1 column data.table

After looking into the code I thought I should try not using the removeFirstG option.. so I tried :

ctss <- getCTSS(mycage,removeFirstG = FALSE,correctSystematicG = FALSE)

and got :

Reading in file: test/test-C_sorted.bam...
	-> Filtering out low quality reads...
Error in `$<-.data.frame`(`*tmp*`, "tag_count", value = 1) : 
  replacement has 1 row, data has 0

So basically got stuck at the same place in the source code, but with a different error.

If I turn only correctSystematicG false, i get the same error :

ctss <- getCTSS(mycage, removeFirstG = TRUE, correctSystematicG = FALSE)

Reading in file: ../rawdata_results/fetish-C_sorted.bam...
	-> Filtering out low quality reads...
	-> Removing the first base of the reads if 'G' and not aligned to the genome...
Error in `$<-.data.frame`(`*tmp*`, "tag_count", value = 1) : 
  replacement has 1 row, data has 0

 

I would appreciate any help with this problem..

Thanks

Vivek

CAGEr cage • 1.4k views
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Vivek.b ▴ 100
@vivekb-7661
Last seen 2.2 years ago
Germany

I solved the problem today. Although it was a silly thing but was hard to catch. The problem was that I mapped my data using ENSEMBL annotation, and had no "chr" in my seqnames. Since the getCTSS methods uses this : 

reads.GRanges <- reads.GRanges[seqnames(reads.GRanges) %in% seqnames(genome)]

It removed all my entries and gives empty Granges. The method throws no warning here and gets stuck at the next step.

I want to request the authors to add a warning here, and also add a way to catch and solve for this chr vs no-chr problem while making the comparison, since others might also face the same issue.

Best,

Vivek

 

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hi, I am using CAGEr too. And  I download the bam file from FANTOM5 website. I got the same problem like you. Can you tell me how to solve the problem?

> input.file <- c("G:/CAGEr1110/Mouse%20Neurons%20-%20striatal%2c%20donor3.CNhs12111.11646-122D8.mm10.nobarcode.bam")
> samples <- "test"
> myCAGEset <- new("CAGEset", genomeName = "BSgenome.Mmusculus.UCSC.mm10",
+                  inputFiles = input.file, inputFilesType = "bam",
+                  sampleLabels = samples)
> getCTSS(myCAGEset)

Reading in file: G:/CAGEr1110/Mouse%20Neurons%20-%20striatal%2c%20donor3.CNhs12111.11646-122D8.mm10.nobarcode.bam...
-> Filtering out low quality reads...
-> Removing the first base of the reads if 'G' and not aligned to the genome...
-> Estimating the frequency of adding a 'G' nucleotide and correcting the systematic bias...
Error in setnames(CTSS, c("chr", "pos", "strand", sample.label)) : 
  Can't assign 4 names to a 1 column data.table

the website I download the  bam file is http://fantom.gsc.riken.jp/5/datafiles/latest/basic/mouse.primary_cell.hCAGE/

by the way the info  of my R is 

> sessionInfo()
R version 3.5.1 (2018-07-02)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows >= 8 x64 (build 9200)

Matrix products: default

locale:
[1] LC_COLLATE=Chinese (Simplified)_China.936  LC_CTYPE=Chinese (Simplified)_China.936    LC_MONETARY=Chinese (Simplified)_China.936
[4] LC_NUMERIC=C                               LC_TIME=Chinese (Simplified)_China.936    

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

other attached packages:
 [1] BSgenome.Mmusculus.UCSC.mm10_1.4.0 BSgenome_1.50.0                    rtracklayer_1.42.0                
 [4] Biostrings_2.50.1                  XVector_0.22.0                     GenomicRanges_1.34.0              
 [7] GenomeInfoDb_1.18.0                IRanges_2.16.0                     S4Vectors_0.20.0                  
[10] BiocGenerics_0.28.0                CAGEr_1.24.0                      

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.0                        stringdist_0.9.5.1                BSgenome.Mmusculus.UCSC.mm9_1.4.0
 [4] lattice_0.20-38                   formula.tools_1.7.1               Rsamtools_1.34.0                 
 [7] gtools_3.8.1                      assertthat_0.2.0                  digest_0.6.18                    
[10] R6_2.3.0                          plyr_1.8.4                        ggplot2_3.1.0                    
[13] pillar_1.3.0                      zlibbioc_1.28.0                   rlang_0.3.0.1                    
[16] lazyeval_0.2.1                    rstudioapi_0.8                    data.table_1.11.8                
[19] vegan_2.5-3                       Matrix_1.2-15                     splines_3.5.1                    
[22] BiocParallel_1.16.0               RCurl_1.95-4.11                   munsell_0.5.0                    
[25] DelayedArray_0.8.0                compiler_3.5.1                    pkgconfig_2.0.2                  
[28] mgcv_1.8-25                       tidyselect_0.2.5                  SummarizedExperiment_1.12.0      
[31] tibble_1.4.2                      GenomeInfoDbData_1.2.0            matrixStats_0.54.0               
[34] XML_3.98-1.16                     reshape_0.8.8                     permute_0.9-4                    
[37] crayon_1.3.4                      dplyr_0.7.7                       GenomicAlignments_1.18.0         
[40] MASS_7.3-51.1                     bitops_1.0-6                      grid_3.5.1                       
[43] nlme_3.1-137                      gtable_0.2.0                      magrittr_1.5                     
[46] scales_1.0.0                      KernSmooth_2.23-15                stringi_1.2.4                    
[49] som_0.3-5.1                       MultiAssayExperiment_1.8.1        bindrcpp_0.2.2                   
[52] tools_3.5.1                       Biobase_2.42.0                    glue_1.3.0                       
[55] purrr_0.2.5                       colorspace_1.3-2                  cluster_2.0.7-1                  
[58] operator.tools_1.6.3              beanplot_1.2                      memoise_1.1.0                    
[61] VGAM_1.0-6                        bindr_0.1.1

thanks  

zhong

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Hi

It's been a while since I had this, but I think the problem was solved by switching the gene annotation to ensembl syle.

seqlevelsStyle(BSgenome.Mmusculus.UCSC.mm10) <- "ENSEMBL"

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Good point with seqlevelsStyle!

I just pushed versions 1.33.1 and 1.32.1 to Bioconductor, which should address these problems.

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Hi, I am also troubled with the problem. If I did not make it wrong, the solution is to redo the mapping of the UCSC GTF file?

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