DESeq2 design help
1
0
Entering edit mode
gitanjali • 0
@8d19db25
Last seen 10 days ago
United States

I have timeseries RNA-seq data that I am trying to analyze using DESeq2. The conditions and time points are as follows:

Condition Rep1 Rep2 Rep3

DMSO 0h 1 2 3

DMSO 1h 1 2 3

DMSO 2h 1 2 3

DMSO 6h 1 2 3

DMSO 24h 1 2 3

Drug1 1h 1 2 3

Drug1 2h 1 2 3

Drug1 6h 1 2 3

Drug1 24h 1 2 3

Drug2 1h 1 2 3

Drug2 2h 1 2 3

Drug2 6h 1 2 3

Drug2 24h 1 2 3

I want to compare the gene expression between the drug and DMSO at each time point (1, 2, 6, 24 hours) and also between the time points. For example, how geneA changes across the time and with different drug treatment. My questions:
1) Is my design correct w.r.t the information I am looking for from my data? 2) How do I extract the results for time.condition?

The design I used :


> deseq_dataset <- DESeqDataSetFromMatrix(countData = count_matrix,

                                colData = sampletable,

                                design = ~ time + condition + time:condition)

> deseq_dataset2 <- DESeq(deseq_dataset, test="LRT", reduced = ~ time + condition)

> resultsNames(deseq_dataset2)

 [1] "Intercept"                  "time_24h_vs_1h"             "time_2h_vs_1h"            

 [4] "time_6h_vs_1h"              "condition_Drug1_vs_DMSO" "condition_Drug2_vs_DMSO"      

 [7] "time24h.conditionDrug1"  "time2h.conditionDrug1"   "time6h.conditionDrug1"  

[10] "time24h.conditionDrug2"        "time2h.conditionDrug2"         "time6h.conditionDrug2"

> # extract results for condition_Drug1_vs_DMSO

> de_Drug1_vs_DMSO <- results(object = deseq_dataset2,

                               name="condition_Drug1_vs_DMSO", contrast = c("condition","Drug1", "DMSO"))
> sessionInfo( )
R version 3.6.3 (2020-02-29)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19042)

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    

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

other attached packages:
 [1] gridExtra_2.3               DOSE_3.12.0                 clusterProfiler_3.14.3     
 [4] org.Mm.eg.db_3.10.0         AnnotationDbi_1.48.0        RColorBrewer_1.1-2         
 [7] pheatmap_1.0.12             biomaRt_2.42.1              forcats_0.5.1              
[10] stringr_1.4.0               dplyr_1.0.5                 purrr_0.3.4                
[13] readr_1.4.0                 tidyr_1.1.3                 tibble_3.1.0               
[16] tidyverse_1.3.0             plotly_4.9.3                ggplot2_3.3.3              
[19] DESeq2_1.26.0               SummarizedExperiment_1.16.1 DelayedArray_0.12.3        
[22] BiocParallel_1.20.1         matrixStats_0.58.0          Biobase_2.46.0             
[25] GenomicRanges_1.38.0        GenomeInfoDb_1.22.1         IRanges_2.20.2             
[28] S4Vectors_0.24.4            BiocGenerics_0.32.0        

loaded via a namespace (and not attached):
  [1] readxl_1.3.1           backports_1.2.1        Hmisc_4.5-0           
  [4] fastmatch_1.1-0        BiocFileCache_1.10.2   plyr_1.8.6            
  [7] igraph_1.2.6           lazyeval_0.2.2         splines_3.6.3         
 [10] urltools_1.7.3         digest_0.6.27          htmltools_0.5.1.1     
 [13] GOSemSim_2.12.1        viridis_0.5.1          GO.db_3.10.0          
 [16] fansi_0.4.2            magrittr_2.0.1         checkmate_2.0.0       
 [19] memoise_2.0.0          cluster_2.1.1          annotate_1.64.0       
 [22] graphlayouts_0.7.1     modelr_0.1.8           askpass_1.1           
 [25] enrichplot_1.6.1       prettyunits_1.1.1      jpeg_0.1-8.1          
 [28] colorspace_2.0-0       blob_1.2.1             rvest_1.0.0           
 [31] rappdirs_0.3.3         ggrepel_0.9.1          haven_2.3.1           
 [34] xfun_0.22              crayon_1.4.1           RCurl_1.98-1.3        
 [37] jsonlite_1.7.2         genefilter_1.68.0      survival_3.2-10       
 [40] glue_1.4.2             polyclip_1.10-0        gtable_0.3.0          
 [43] zlibbioc_1.32.0        XVector_0.26.0         scales_1.1.1          
 [46] DBI_1.1.1              Rcpp_1.0.6             viridisLite_0.3.0     
 [49] xtable_1.8-4           progress_1.2.2         htmlTable_2.1.0       
 [52] gridGraphics_0.5-1     europepmc_0.4          foreign_0.8-75        
 [55] bit_4.0.4              Formula_1.2-4          htmlwidgets_1.5.3     
 [58] httr_1.4.2             fgsea_1.12.0           ellipsis_0.3.1        
 [61] pkgconfig_2.0.3        XML_3.99-0.3           farver_2.1.0          
 [64] nnet_7.3-15            dbplyr_2.1.1           locfit_1.5-9.4        
 [67] utf8_1.2.1             ggplotify_0.0.5        tidyselect_1.1.0      
 [70] rlang_0.4.10           reshape2_1.4.4         munsell_0.5.0         
 [73] cellranger_1.1.0       tools_3.6.3            cachem_1.0.4          
 [76] cli_2.4.0              generics_0.1.0         RSQLite_2.2.5         
 [79] ggridges_0.5.3         broom_0.7.6            fastmap_1.1.0         
 [82] knitr_1.31             bit64_4.0.5            fs_1.5.0              
 [85] tidygraph_1.2.0        ggraph_2.0.5           DO.db_2.9             
 [88] xml2_1.3.2             compiler_3.6.3         rstudioapi_0.13       
 [91] curl_4.3               png_0.1-7              reprex_2.0.0          
 [94] tweenr_1.0.2           geneplotter_1.64.0     stringi_1.5.3         
 [97] lattice_0.20-41        Matrix_1.3-2           vctrs_0.3.7           
[100] pillar_1.5.1           lifecycle_1.0.0        BiocManager_1.30.12   
[103] triebeard_0.3.0        cowplot_1.1.1          data.table_1.14.0     
[106] bitops_1.0-6           qvalue_2.18.0          R6_2.5.0              
[109] latticeExtra_0.6-29    MASS_7.3-53.1          assertthat_0.2.1      
[112] openssl_1.4.3          withr_2.4.1            GenomeInfoDbData_1.2.2
[115] hms_1.0.0              rpart_4.1-15           rvcheck_0.1.8         
[118] ggforce_0.3.3          lubridate_1.7.10       base64enc_0.1-3
DESeq2 • 111 views
ADD COMMENT
0
Entering edit mode
@mikelove
Last seen 10 hours ago
United States

See my answer to this other recent post re: support on statistical analysis and results interpretation:

Multi-factor Analysis in DeSEQ2

ADD COMMENT

Login before adding your answer.

Traffic: 452 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6