Error using DESeq2's nbinomLRT
Entering edit mode
guyho ▴ 20
Last seen 4 months ago


I have a 2 factor experiment (2 mutations:A,B), with 2 levels (+/-) in each factor. All together there 4 conditions: wt, A, B, and A+B , with two replicates for each condition. I tried to use LRT test to isolate genes that are correspond to the mutations without interaction. the full model I used is ~A+B+A:B and the reduced is ~A:B I received the following error:

Error in nbinomLRT(object, full = full, reduced = reduced, quiet = quiet,  : 
  less than one degree of freedom, perhaps full and reduced models are not in the correct order

why are the degrees of freedom less than 1? Below I pasted the sessionInfo output. Thanks in advance.


R version 4.0.2 (2020-06-22)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 18362)

Matrix products: default

Random number generation:
 RNG:     Mersenne-Twister 
 Normal:  Inversion 
 Sample:  Rounding 

[1] LC_COLLATE=English_United States.1252 
[2] LC_CTYPE=English_United States.1252   
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.1252    

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

other attached packages:
 [1] ggplotify_0.0.5             gridExtra_2.3              
 [3] dplyr_1.0.0                 DESeq2_1.28.1              
 [5] SummarizedExperiment_1.18.1 DelayedArray_0.14.0        
 [7] matrixStats_0.56.0          Biobase_2.48.0             
 [9] GenomicRanges_1.40.0        GenomeInfoDb_1.24.2        
[11] IRanges_2.22.2              S4Vectors_0.26.1           
[13] BiocGenerics_0.34.0         ggplot2_3.3.2              
[15] readxl_1.3.1                data.table_1.12.8          

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.4.6           locfit_1.5-9.4        
 [3] lattice_0.20-41        assertthat_0.2.1      
 [5] digest_0.6.25          R6_2.4.1              
 [7] cellranger_1.1.0       RSQLite_2.2.0         
 [9] pillar_1.4.4           zlibbioc_1.34.0       
[11] rlang_0.4.6            rstudioapi_0.11       
[13] annotate_1.66.0        blob_1.2.1            
[15] Matrix_1.2-18          labeling_0.3          
[17] splines_4.0.2          BiocParallel_1.22.0   
[19] geneplotter_1.66.0     pheatmap_1.0.12       
[21] RCurl_1.98-1.2         bit_1.1-15.2          
[23] munsell_0.5.0          compiler_4.0.2        
[25] pkgconfig_2.0.3        gridGraphics_0.5-0    
[27] tidyselect_1.1.0       tibble_3.0.1          
[29] GenomeInfoDbData_1.2.3 XML_3.99-0.4          
[31] fansi_0.4.1            crayon_1.3.4          
[33] withr_2.2.0            bitops_1.0-6          
[35] xtable_1.8-4           gtable_0.3.0          
[37] lifecycle_0.2.0        DBI_1.1.0             
[39] magrittr_1.5           scales_1.1.1          
[41] cli_2.0.2              farver_2.0.3          
[43] XVector_0.28.0         genefilter_1.70.0     
[45] ellipsis_0.3.1         rvcheck_0.1.8         
[47] generics_0.0.2         vctrs_0.3.1           
[49] RColorBrewer_1.1-2     tools_4.0.2           
[51] bit64_0.9-7            glue_1.4.1            
[53] purrr_0.3.4            survival_3.1-12       
[55] AnnotationDbi_1.50.1   colorspace_1.4-1      
[57] BiocManager_1.30.10    memoise_1.1.0
deseq2 LRT • 171 views
Entering edit mode
Last seen 15 hours ago
United States

The reduced model is the null model, but here you've removed the main effects and left only the interaction. Take a look at the LRT section of the vignette.

Entering edit mode

Thanks for the help.

So to find genes affected only by mutation A (and not by mutation B or interaction) should I: 1)test full=~A+B+A:B, reduced=~1 2)test full=~A+B+A:B, reduced=~A+B 3) test full=~A+B, reduced=~B

Select genes significant in 1 and not significant in 2 and 3?

Entering edit mode

I'd recommend collaborating with a statistician to work out the right statistical design for your experiment. We have a lot of material in the vignette, but beyond that I unfortunately don't have time to provide statistical consultation on the support site.


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