Hi! I already asked this, but was combined with another question, therefore I missed the answer I was looking.

I have my DeseqDataSet which I want to put in Reporting tools -> dds

out <- "/mnt/out/"
des2ReportAll <- HTMLReport(shortName = 'RNAseq_analysis_with_DESeq2', title = 'sRNA-seq using DESeq2, pvalue cutoff None', basePath = out, reportDirectory = 'html/')


publish(dds, des2ReportAll, pvalueCutoff=2, annotation.db="org.Hs.egENSEMBL", coef = 3,factor = colData(dds)$condition, reportDir=out, n = length(row.names(dds))) 
        #.modifyDF=makeDESeqDF) ##I tried this for the results(dds) but did not work 

This is what I use for creating the html report. I would like to include every single gene from the dds into my html (not from the result, because i would like the normalized countings ploted and not the FC), therefore I do not want to filter via pvalue or anything, I would like to have the report of everything. I am wondering where can I specify this.

Thank you, 

> sessionInfo()
R version 3.3.0 (2016-05-03)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Debian GNU/Linux 8 (jessie)

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

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

other attached packages:
 [1] ReportingTools_2.12.2      knitr_1.13                 pheatmap_1.0.8             stringr_1.0.0             
 [5] RColorBrewer_1.1-2         DESeq2_1.12.3              SummarizedExperiment_1.2.3 GenomicRanges_1.24.2      
 [9] GenomeInfoDb_1.8.1         ggplot2_2.1.0              geneplotter_1.50.0         annotate_1.50.0           
[13] XML_3.98-1.4               lattice_0.20-33            genefilter_1.54.2          AnnotationDbi_1.34.3      
[17] IRanges_2.6.1              S4Vectors_0.10.1           Biobase_2.32.0             BiocGenerics_0.18.0       
[21] scatterplot3d_0.3-37      

loaded via a namespace (and not attached):
 [1] httr_1.2.0                    edgeR_3.14.0                  AnnotationHub_2.4.2          
 [4] splines_3.3.0                 R.utils_2.3.0                 Formula_1.2-1                
 [7] shiny_0.13.2                  interactiveDisplayBase_1.10.3 latticeExtra_0.6-28          
[10] RBGL_1.48.1                   BSgenome_1.40.1               Rsamtools_1.24.0             
[13] Category_2.38.0               RSQLite_1.0.0                 biovizBase_1.20.0            
[16] limma_3.28.10                 chron_2.3-47                  digest_0.6.9                 
[19] XVector_0.12.0                colorspace_1.2-6              ggbio_1.20.1                 
[22] R.oo_1.20.0                   httpuv_1.3.3                  htmltools_0.3.5              
[25] Matrix_1.2-6                  plyr_1.8.4                    OrganismDbi_1.14.1           
[28] GSEABase_1.34.0               biomaRt_2.28.0                zlibbioc_1.18.0              
[31] xtable_1.8-2                  GO.db_3.3.0                   scales_0.4.0                 
[34] BiocParallel_1.6.2            PFAM.db_3.3.0                 GenomicFeatures_1.24.2       
[37] nnet_7.3-12                   mime_0.4                      survival_2.39-4              
[40] magrittr_1.5                  R.methodsS3_1.7.1             GGally_1.1.0                 
[43] hwriter_1.3.2                 foreign_0.8-66                GOstats_2.38.0               
[46] BiocInstaller_1.22.3          graph_1.50.0                  tools_3.3.0                  
[49] data.table_1.9.6              munsell_0.4.3                 locfit_1.5-9.1               
[52] cluster_2.0.4                 ensembldb_1.4.6               Biostrings_2.40.2            
[55] grid_3.3.0                    RCurl_1.95-4.8                dichromat_2.0-0              
[58] VariantAnnotation_1.18.1      AnnotationForge_1.14.2        bitops_1.0-6                 
[61] gtable_0.2.0                  DBI_0.4-1                     reshape_0.8.5                
[64] reshape2_1.4.1                R6_2.1.2                      GenomicAlignments_1.8.3      
[67] gridExtra_2.2.1               rtracklayer_1.32.1            Hmisc_3.17-4                 
[70] stringi_1.1.1                 Rcpp_0.12.5                   rpart_4.1-10                 
[73] acepack_1.3-3.3  

Can you try making the report with this publish method? Note that you can provide both object (a DESeqResults table) and DataSet (a DESeqDataSet), and it should make the stripplots.

DESeqResults: publish(object, publicationType, DataSet = NULL, annotation.db = NULL, n = 500, pvalueCutoff = 0.01, lfc = 0, make.plots = TRUE, ..., name)
To coerce a DESeqResults object to a data.frame, we filter the results DataFrame such
that the absolute log fold changes is greater than lfc and the adjusted p-value is less than
pvalueCutoff. If present, annotation.db is used to find gene-level annotations for the rows
in the DESeqResults. If make.plots is TRUE, stripplots showing the expression values for
each transcript are produced based on the normalized counts from the DataSet, which should
be of class DESeqDataSet, grouped by the levels in factor.