Generate a HTML/PDF report exploring DESeq2 results

This function generates a HTML report with exploratory data analysis plots for DESeq2 results created with DESeq. Other output formats are possible such as PDF but lose the interactivity. Users can easily append to the report by providing a R Markdown file to customCode, or can customize the entire template by providing an R Markdown file to template.

DESeq2Report(
  dds,
  project = "",
  intgroup,
  colors = NULL,
  res = NULL,
  nBest = 500,
  nBestFeatures = 20,
  customCode = NULL,
  outdir = "DESeq2Exploration",
  output = "DESeq2Exploration",
  browse = interactive(),
  device = "png",
  template = NULL,
  searchURL = "http://www.ncbi.nlm.nih.gov/gene/?term=",
  theme = NULL,
  digits = 2,
  ...
)

Arguments

dds

A DESeqDataSet object with the results from running DESeq.

project

The title of the project.

intgroup

interesting groups: a character vector of names in colData(x) to use for grouping. This parameter is passed to functions such as plotPCA.

colors

vector of colors used in heatmap. If NULL, then a a default set of colors will be used. This argument is passed to pheatmap.

res

A DESeqResults object. If NULL, then results will be used on dds with default parameters.

nBest

The number of features to include in the interactive table. Features are ordered by their adjusted p-values.

nBestFeatures

The number of best features to make plots of their counts. We recommend a small number, say 20.

customCode

An absolute path to a child R Markdown file with code to be evaluated before the reproducibility section. Its useful for users who want to customize the report by adding conclusions derived from the data and/or further quality checks and plots.

outdir

The name of output directory.

output

The name of output HTML file (without the html extension).

browse

If TRUE the HTML report is opened in your browser once it's completed.

device

The graphical device used when knitting. See more at http://yihui.name/knitr/options (dev argument).

template

Template file to use for the report. If not provided, will use the default file found in DESeq2Exploration/DESeq2Exploration.Rmd within the package source.

searchURL

A url used for searching the name of the features in the web. By default http://www.ncbi.nlm.nih.gov/gene/?term= is used which is the recommended option when features are genes. It's only used when the output is a HTML file.

theme

A ggplot2 theme to use for the plots made with ggplot2.

digits

The number of digits to round to in the interactive table of the top nBestFeatures. Note that p-values and adjusted p-values won't be rounded.

...

Arguments passed to other methods and/or advanced arguments. Advanced arguments:

software

The name of the package used for performing the differential expression analysis. Either DESeq2 or edgeR.

dge

A DGEList object. NULL by default and only used by edgeReport.

theCall

The function call. NULL by default and only used by edgeReport.

output_format

Either html_document, pdf_document or knitrBootstrap::bootstrap_document unless you modify the YAML template.

clean

Logical, whether to clean the results or not. Passed to render.

Value

An HTML report with a basic exploration for the given set of DESeq2 results. See an example at http://leekgroup.github.io/regionReport/reference/DESeq2Report-example/DESeq2Exploration.html.

Details

Set output_format to 'knitrBootstrap::bootstrap_document' or 'pdf_document' if you want a HTML report styled by knitrBootstrap or a PDF report respectively. If using knitrBootstrap, we recommend the version available only via GitHub at https://github.com/jimhester/knitrBootstrap which has nicer features than the current version available via CRAN. You can also set the output_format to 'html_document' for a HTML report styled by rmarkdown. The default is set to 'BiocStyle::html_document'.

If you modify the YAML front matter of template, you can use other values for output_format.

The HTML report styled with knitrBootstrap can be smaller in size than the 'html_document' report.

Author

Leonardo Collado-Torres

Examples

## Load example data from the pasilla package as done in the DESeq2 vignette
## at
## <https://bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#count-matrix-input>.
library("pasilla")
#> Loading required package: DEXSeq
#> Loading required package: BiocParallel
#> Loading required package: Biobase
#> Loading required package: BiocGenerics
#> 
#> Attaching package: ‘BiocGenerics’
#> The following objects are masked from ‘package:stats’:
#> 
#>     IQR, mad, sd, var, xtabs
#> The following objects are masked from ‘package:base’:
#> 
#>     Filter, Find, Map, Position, Reduce, anyDuplicated, aperm, append,
#>     as.data.frame, basename, cbind, colnames, dirname, do.call,
#>     duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
#>     lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
#>     pmin.int, rank, rbind, rownames, sapply, saveRDS, setdiff, table,
#>     tapply, union, unique, unsplit, which.max, which.min
#> Welcome to Bioconductor
#> 
#>     Vignettes contain introductory material; view with
#>     'browseVignettes()'. To cite Bioconductor, see
#>     'citation("Biobase")', and for packages 'citation("pkgname")'.
#> Loading required package: SummarizedExperiment
#> Loading required package: MatrixGenerics
#> Loading required package: matrixStats
#> 
#> Attaching package: ‘matrixStats’
#> The following objects are masked from ‘package:Biobase’:
#> 
#>     anyMissing, rowMedians
#> 
#> Attaching package: ‘MatrixGenerics’
#> The following objects are masked from ‘package:matrixStats’:
#> 
#>     colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,
#>     colCounts, colCummaxs, colCummins, colCumprods, colCumsums,
#>     colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,
#>     colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
#>     colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,
#>     colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,
#>     colWeightedMeans, colWeightedMedians, colWeightedSds,
#>     colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,
#>     rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,
#>     rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
#>     rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,
#>     rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
#>     rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,
#>     rowWeightedMads, rowWeightedMeans, rowWeightedMedians,
#>     rowWeightedSds, rowWeightedVars
#> The following object is masked from ‘package:Biobase’:
#> 
#>     rowMedians
#> Loading required package: GenomicRanges
#> Loading required package: stats4
#> Loading required package: S4Vectors
#> 
#> Attaching package: ‘S4Vectors’
#> The following object is masked from ‘package:utils’:
#> 
#>     findMatches
#> The following objects are masked from ‘package:base’:
#> 
#>     I, expand.grid, unname
#> Loading required package: IRanges
#> Loading required package: GenomeInfoDb
#> Loading required package: DESeq2
#> Loading required package: AnnotationDbi
#> Loading required package: RColorBrewer
pasCts <- system.file("extdata",
    "pasilla_gene_counts.tsv",
    package = "pasilla", mustWork = TRUE
)
pasAnno <- system.file("extdata",
    "pasilla_sample_annotation.csv",
    package = "pasilla", mustWork = TRUE
)
cts <- as.matrix(read.csv(pasCts, sep = "\t", row.names = "gene_id"))
coldata <- read.csv(pasAnno, row.names = 1)
coldata <- coldata[, c("condition", "type")]
coldata$condition <- factor(coldata$condition)
coldata$type <- factor(coldata$type)
rownames(coldata) <- sub("fb", "", rownames(coldata))
cts <- cts[, rownames(coldata)]

## Create DESeqDataSet object from the pasilla package
library("DESeq2")
dds <- DESeqDataSetFromMatrix(
    countData = cts,
    colData = coldata,
    design = ~condition
)
dds <- DESeq(dds)
#> estimating size factors
#> estimating dispersions
#> gene-wise dispersion estimates
#> mean-dispersion relationship
#> final dispersion estimates
#> fitting model and testing

## The output will be saved in the 'DESeq2Report-example' directory
dir.create("DESeq2Report-example", showWarnings = FALSE, recursive = TRUE)

## Generate the HTML report
report <- DESeq2Report(dds, "DESeq2-example", c("condition", "type"),
    outdir = "DESeq2Report-example"
)
#> Writing 9 Bibtex entries ... 
#> OK
#> Results written to file ‘DESeq2Report-example/DESeq2Exploration.bib’
#> 
#> 
#> processing file: DESeq2Exploration.Rmd
#> 1/47                    
#> 2/47 [docSetup]         
#> 3/47                    
#> 4/47 [setup]            
#> 5/47                    
#> 6/47 [PCA]              
#> 7/47                    
#> 8/47 [sampleDist]       
#> 9/47                    
#> 10/47 [MAplotalpha]      
#> 11/47                    
#> 12/47 [MAplotalphaHalf]  
#> 13/47                    
#> 14/47 [MAplotalpha-nBest]
#> 15/47                    
#> 16/47 [pvalueHistogram]  
#> 17/47                    
#> 18/47 [pvalueSumm]       
#> 19/47                    
#> 20/47 [pvalueTable]      
#> 21/47                    
#> 22/47 [padjHistogram]    
#> 23/47                    
#> 24/47 [padjSumm]         
#> 25/47                    
#> 26/47 [padjTable]        
#> 27/47                    
#> 28/47 [topFeatures]      
#> 29/47                    
#> 30/47 [plotCounts]       

#> 31/47                    
#> 32/47 [edgeR-BCV]        
#> 33/47                    
#> 34/47 [edgeR-MDS]        
#> 35/47                    
#> 36/47 [unnamed-chunk-1]  
#> 37/47                    
#> 38/47 [thecall]          
#> 39/47                    
#> 40/47 [reproducibility1] 
#> 41/47                    
#> 42/47 [reproducibility2] 
#> 43/47                    
#> 44/47 [reproducibility3] 
#> 45/47                    
#> 46/47 [bibliography]     
#> 47/47                    
#> output file: DESeq2Exploration.knit.md
#> /usr/bin/pandoc +RTS -K512m -RTS DESeq2Exploration.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output DESeq2Exploration.html --lua-filter /__w/_temp/Library/bookdown/rmarkdown/lua/custom-environment.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/table-classes.lua --embed-resources --standalone --wrap preserve --variable bs3=TRUE --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /tmp/RtmplloSdM/BiocStyle/template.html --no-highlight --variable highlightjs=1 --number-sections --variable theme=bootstrap --css /__w/_temp/Library/BiocStyle/resources/html/bioconductor.css --mathjax --variable 'mathjax-url=https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --include-in-header /tmp/RtmplloSdM/rmarkdown-str9b331c17d83.html --variable code_folding=hide --variable code_menu=1 
#> 
#> Output created: DESeq2Exploration.html

if (interactive()) {
    ## Browse the report
    browseURL(report)
}

## See the example output at
## http://leekgroup.github.io/regionReport/reference/DESeq2Report-example/DESeq2Exploration.html
if (FALSE) { # \dontrun{
## Note that you can run the example using:
example("DESeq2Report", "regionReport", ask = FALSE)
} # }