danko-lab / rtfbs_db Goto Github PK

> tfs2 <- tfbs.selectExpressedMotifs(tfs,
+                                   file.hg19.twobit.chr19, 
+                                   file.gencode.gtf.chr19, 
+                                   file.bigwig.plus.chr19, 
+                                   file.bigwig.minus.chr19, 
+                                   pvalue.threshold=0.001,
+                                   include.DBID.missing=TRUE,
+                                   lowest.reads.RPKM=5,
+                                   seq.datatype="PRO-seq");
  12758 transcripts are selected from GENCODE dataset for PRO-seq .
  13591245 Reads in /home/gvillafano/R/x86_64-pc-linux-gnu-library/3.3/rtfbsdb/extdata/GSM1480327_K562_PROseq_chr19_plus.bw and /home/gvillafano/R/x86_64-pc-linux-gnu-library/3.3/rtfbsdb/extdata/GSM1480327_K562_PROseq_chr19_minus.bw 
* 1851 motifs did not find DBID in the Gencode file.
* 1957 expressed TFs are selected from 1964 motifs after filtering by the gene expression.
> tfs <- tfbs.clusterMotifs(tfs2, method="agnes", pdf.heatmap="heatmap.pdf", ncores=11)
Error in 1 - mat : non-numeric argument to binary operator
In addition: Warning message:
In mclapply(1:tfbs@ntfs, function(i) { :
  all scheduled cores encountered errors in user code

> sum(sapply(tfs2@pwm, is.null))
[1] 1851

> sessionInfo()
R version 3.3.2 (2016-10-31)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 16.04.2 LTS

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

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

other attached packages:
 [1] rGADEM_2.22.0        seqLogo_1.40.0       BSgenome_1.42.0      rtracklayer_1.34.2  
 [5] TFBSTools_1.12.2     rtfbsdb_0.4.0        Biostrings_2.42.1    XVector_0.14.1      
 [9] GenomicRanges_1.26.4 GenomeInfoDb_1.10.3  IRanges_2.8.2        S4Vectors_0.12.2    
[13] BiocGenerics_0.20.0 

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.10                lattice_0.20-34             GO.db_3.4.0                
 [4] png_0.1-7                   Rsamtools_1.26.2            gtools_3.5.0               
 [7] digest_0.6.12               R6_2.2.0                    plyr_1.8.4                 
[10] RSQLite_1.1-2               httr_1.2.1                  ggplot2_2.2.1              
[13] zlibbioc_1.20.0             lazyeval_0.2.0              annotate_1.52.1            
[16] rtfbs_0.3.5                 R.utils_2.5.0               R.oo_1.21.0                
[19] Matrix_1.2-8                apcluster_1.4.3             splines_3.3.2              
[22] BiocParallel_1.8.2          readr_1.1.0                 stringr_1.2.0              
[25] CNEr_1.10.2                 bigWig_0.2-9                RCurl_1.95-4.8             
[28] munsell_0.4.3               DirichletMultinomial_1.16.0 SummarizedExperiment_1.4.0 
[31] KEGGREST_1.14.1             tibble_1.3.0                XML_3.98-1.6               
[34] TFMPvalue_0.0.6             GenomicAlignments_1.10.1    bitops_1.0-6               
[37] R.methodsS3_1.7.1           xtable_1.8-2                gtable_0.2.0               
[40] DBI_0.6-1                   magrittr_1.5                scales_0.4.1               
[43] stringi_1.1.5               reshape2_1.4.2              latticeExtra_0.6-28        
[46] vioplot_0.2                 RColorBrewer_1.1-2          tools_3.3.2                
[49] Biobase_2.34.0              poweRlaw_0.70.0             hms_0.3                    
[52] rphast_1.6.5                AnnotationDbi_1.36.2        colorspace_1.3-2           
[55] cluster_2.0.6               caTools_1.17.1              memoise_1.0.0              
[58] VGAM_1.0-3                 
>