The results(dds) function in DESeq2 gives Na values for padj
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Entering edit mode
@d5e202c8
Last seen 5 weeks ago
Germany

The results(dds) function in DESeq2 gives Na values for padj, which I find quite puzzling. From what I understand, In principle, if the pval is there, the adjusted pval should not be NA. I checked the entire column of pvalue and there is no NA value.

As a Example,

res <- results(dds1)
head(res, 30)

The output is :

log2 fold change (MLE): condition Infected vs control 
Wald test p-value: condition Infected vs control 
DataFrame with 30 rows and 6 columns
                      baseMean log2FoldChange     lfcSE       stat    pvalue      padj
                     <numeric>      <numeric> <numeric>  <numeric> <numeric> <numeric>
ENSMUSG00000102628 1.14237e-01       0.425855  5.143224  0.0827992  0.934011        NA
ENSMUSG00000100595 1.03784e+00       2.596535  2.155339  1.2046989  0.228320        NA
ENSMUSG00000097426 8.81255e-02       0.273996  5.143224  0.0532733  0.957514        NA
ENSMUSG00000104385 2.75549e-01      -1.871954  2.382787 -0.7856153  0.432093        NA
ENSMUSG00000102135 1.30991e+03       0.191029  0.158737  1.2034269  0.228811  0.543587
...                        ...            ...       ...        ...       ...       ...
ENSMUSG00000090243    0.281665      -0.668478  2.563541  -0.260764 0.7942747        NA
ENSMUSG00000100701    0.720093       2.086543  4.345479   0.480164 0.6311107        NA
ENSMUSG00000100555   66.338703      -0.624417  0.359642  -1.736216 0.0825256  0.339681
ENSMUSG00000038702   53.606263      -0.185831  0.253518  -0.733010 0.4635526  0.738668
ENSMUSG00000101875  386.361469       0.304486  0.178201   1.708662 0.0875137  0.349655

In case you want to take a look at the entire results table , then here it is : https://github.com/MysoreSparrow/AZB_DataAnalysis/blob/main/results.csv.

sessionInfo( )
R version 4.1.3 (2022-03-10)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 22000)

Matrix products: default

locale:
[1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United States.1252   
[3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C                          
[5] LC_TIME=English_United States.1252    
system code page: 65001

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

other attached packages:
 [1] apeglm_1.16.0               BiocManager_1.30.16         glmpca_0.2.0               
 [4] genefilter_1.76.0           org.Mm.eg.db_3.14.0         AnnotationDbi_1.56.2       
 [7] gplots_3.1.3                EnhancedVolcano_1.12.0      ggrepel_0.9.1              
[10] vsn_3.62.0                  forcats_0.5.1               stringr_1.4.0              
[13] dplyr_1.0.9                 purrr_0.3.4                 readr_2.1.2                
[16] tidyr_1.2.0                 tibble_3.1.7                ggplot2_3.3.6              
[19] tidyverse_1.3.1             RColorBrewer_1.1-3          pheatmap_1.0.12            
[22] PoiClaClu_1.0.2.1           DESeq2_1.34.0               SummarizedExperiment_1.24.0
[25] Biobase_2.54.0              MatrixGenerics_1.6.0        matrixStats_0.62.0         
[28] GenomicRanges_1.46.1        GenomeInfoDb_1.30.1         IRanges_2.28.0             
[31] S4Vectors_0.32.4            BiocGenerics_0.40.0      

loaded via a namespace (and not attached):
  [1] ggbeeswarm_0.6.0       colorspace_2.0-3       ellipsis_0.3.2         XVector_0.34.0        
  [5] fs_1.5.2               rstudioapi_0.13        farver_2.1.0           hexbin_1.28.2         
  [9] affyio_1.64.0          bit64_4.0.5            mvtnorm_1.1-3          fansi_1.0.3           
 [13] lubridate_1.8.0        xml2_1.3.3             splines_4.1.3          extrafont_0.18        
 [17] cachem_1.0.6           geneplotter_1.72.0     knitr_1.39             jsonlite_1.8.0        
 [21] Rttf2pt1_1.3.10        broom_0.8.0            annotate_1.72.0        dbplyr_2.1.1          
 [25] png_0.1-7              compiler_4.1.3         httr_1.4.3             backports_1.4.1       
 [29] assertthat_0.2.1       Matrix_1.4-0           fastmap_1.1.0          limma_3.50.3          
 [33] cli_3.2.0              htmltools_0.5.2        tools_4.1.3            coda_0.19-4           
 [37] gtable_0.3.0           glue_1.6.2             GenomeInfoDbData_1.2.7 affy_1.72.0           
 [41] maps_3.4.0             Rcpp_1.0.8.3           bbmle_1.0.25           cellranger_1.1.0      
 [45] vctrs_0.4.1            Biostrings_2.62.0      ggalt_0.4.0            preprocessCore_1.56.0 
 [49] extrafontdb_1.0        xfun_0.30              rvest_1.0.2            lifecycle_1.0.1       
 [53] gtools_3.9.2           XML_3.99-0.9           zlibbioc_1.40.0        MASS_7.3-55           
 [57] scales_1.2.0           ragg_1.2.2             hms_1.1.1              parallel_4.1.3        
 [61] proj4_1.0-11           yaml_2.3.5             memoise_2.0.1          ggrastr_1.0.1         
 [65] emdbook_1.3.12         bdsmatrix_1.3-4        stringi_1.7.6          RSQLite_2.2.14        
 [69] caTools_1.18.2         BiocParallel_1.28.3    systemfonts_1.0.4      rlang_1.0.2           
 [73] pkgconfig_2.0.3        bitops_1.0-7           evaluate_0.15          lattice_0.20-45       
 [77] labeling_0.4.2         bit_4.0.4              tidyselect_1.1.2       plyr_1.8.7            
 [81] magrittr_2.0.3         R6_2.5.1               generics_0.1.2         DelayedArray_0.20.0   
 [85] DBI_1.1.2              pillar_1.7.0           haven_2.5.0            withr_2.5.0           
 [89] survival_3.2-13        KEGGREST_1.34.0        RCurl_1.98-1.6         ash_1.0-15            
 [93] modelr_0.1.8           crayon_1.5.1           KernSmooth_2.23-20     utf8_1.2.2            
 [97] tzdb_0.3.0             rmarkdown_2.14         locfit_1.5-9.5         grid_4.1.3            
[101] readxl_1.4.0           blob_1.2.3             reprex_2.0.1           digest_0.6.29         
[105] xtable_1.8-4           numDeriv_2016.8-1.1    textshaping_0.3.6      munsell_0.5.0         
[109] beeswarm_0.4.0         vipor_0.4.5
DESeq2 • 151 views
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Entering edit mode
ATpoint ★ 1.3k
@atpoint-13662
Last seen 14 hours ago
Germany

Read the manual: https://bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#why-are-some-p-values-set-to-na

Or check existing posts via google -- it has been asked many times before DESeq2: thousands of NA for pvalues?

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