DESeq2 memory allocation question
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rbronste ▴ 60
@rbronste-12189
Last seen 2.2 years ago

Looking to reallocate more application memory to DESeq2 because when running:

betaPrior = TRUE

On a large matrix, I run out of application memory. Anyone have ideas how to get around this on a Mac (Quad Core w/ 16gb RAM)? Thanks!

deseq2 memory problem • 451 views
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swbarnes2 ▴ 970
@swbarnes2-14086
Last seen 5 hours ago
San Diego

The simple solution is to make your matrix smaller, by getting rid of genes that are unlikely to be interesting, either because their counts are too low to be reliable, or because they don't vary much across samples.  

 

dds <-dds[rowSums(counts(dds)) > whateverFilterNumber,]

 

Is a dead simple way to do this.  There are others.

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I am actually already doing this (135k in matrix after reduction), however following this command:

dds <- DESeq(dds, betaPrior = TRUE, fitType = c("local"), parallel = TRUE)

It tells me Im out of application memory right at the end of DESeq, sometimes even shutting off my computer.

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> sessionInfo()
R version 3.4.1 (2017-06-30)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Sierra 10.12.5

Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

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

other attached packages:
 [1] DiffBind_2.4.8             ggplot2_3.0.0              DESeq2_1.16.1              SummarizedExperiment_1.6.5 DelayedArray_0.2.7        
 [6] matrixStats_0.54.0         Biobase_2.36.2             GenomicRanges_1.28.6       GenomeInfoDb_1.12.3        IRanges_2.10.5            
[11] S4Vectors_0.14.7           BiocGenerics_0.22.1        BiocParallel_1.10.1       

loaded via a namespace (and not attached):
  [1] Category_2.42.1          bitops_1.0-6             bit64_0.9-7              RColorBrewer_1.1-2       tools_3.4.1              backports_1.1.2         
  [7] R6_2.3.0                 rpart_4.1-13             KernSmooth_2.23-15       Hmisc_4.1-1              DBI_1.0.0                lazyeval_0.2.1          
 [13] colorspace_1.3-2         nnet_7.3-12              withr_2.1.2              tidyselect_0.2.5         gridExtra_2.3            bit_1.1-14              
 [19] compiler_3.4.1           sendmailR_1.2-1          graph_1.54.0             htmlTable_1.12           rtracklayer_1.36.6       caTools_1.17.1.1        
 [25] scales_1.0.0             checkmate_1.8.5          BatchJobs_1.7            genefilter_1.58.1        RBGL_1.52.0              stringr_1.3.1           
 [31] digest_0.6.18            Rsamtools_1.28.0         foreign_0.8-71           AnnotationForge_1.18.2   XVector_0.16.0           base64enc_0.1-3         
 [37] pkgconfig_2.0.2          htmltools_0.3.6          limma_3.32.10            htmlwidgets_1.3          rlang_0.2.2              rstudioapi_0.8          
 [43] RSQLite_2.1.1            BBmisc_1.11              GOstats_2.42.0           bindr_0.1.1              hwriter_1.3.2            gtools_3.5.0            
 [49] acepack_1.4.1            dplyr_0.7.6              RCurl_1.95-4.11          magrittr_1.5             GO.db_3.4.1              GenomeInfoDbData_0.99.0 
 [55] Formula_1.2-3            Matrix_1.2-14            Rcpp_0.12.19             munsell_0.5.0            stringi_1.2.4            yaml_2.2.0              
 [61] edgeR_3.18.1             zlibbioc_1.22.0          gplots_3.0.1             plyr_1.8.4               grid_3.4.1               blob_1.1.1              
 [67] ggrepel_0.8.0            gdata_2.18.0             crayon_1.3.4             lattice_0.20-35          Biostrings_2.44.2        splines_3.4.1           
 [73] GenomicFeatures_1.28.5   annotate_1.54.0          locfit_1.5-9.1           knitr_1.20               pillar_1.3.0             rjson_0.2.20            
 [79] systemPipeR_1.10.2       geneplotter_1.54.0       biomaRt_2.32.1           XML_3.98-1.16            glue_1.3.0               ShortRead_1.34.2        
 [85] latticeExtra_0.6-28      data.table_1.11.8        gtable_0.2.0             purrr_0.2.5              amap_0.8-16              assertthat_0.2.0        
 [91] xtable_1.8-3             survival_2.42-6          pheatmap_1.0.10          tibble_1.4.2             GenomicAlignments_1.12.2 AnnotationDbi_1.38.2    
 [97] memoise_1.1.0            bindrcpp_0.2.2           cluster_2.0.7-1          brew_1.0-6               GSEABase_1.38.2 
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@mikelove
Last seen 23 hours ago
United States

Can you provide some details on the samples?

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