edgeReport | R Documentation |
This function generates a HTML report with exploratory data analysis plots
for edgeR results created. Other output formats are possible such as PDF
reports but they 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
.
edgeReport(
dge,
object,
project = "",
intgroup,
colors = NULL,
pAdjustMethod = "BH",
alpha = 0.1,
independentFiltering = FALSE,
filter,
theta,
filterFun,
nBest = 500,
nBestFeatures = 20,
customCode = NULL,
outdir = "edgeRexploration",
output = "edgeRexploration",
browse = interactive(),
device = "png",
template = NULL,
searchURL = "http://www.ncbi.nlm.nih.gov/gene/?term=",
theme = NULL,
digits = 2,
...
)
dge |
A DGEList object. |
object |
A DGEExact or
DGELRT object that contains p-values stored in
|
project |
The title of the project. |
intgroup |
interesting groups: a character vector of names in
|
colors |
vector of colors used in heatmap. If |
pAdjustMethod |
the method to use for adjusting p-values, see p.adjust. This argument will be passed to results. |
alpha |
the significance cutoff used for optimizing the independent filtering (by default 0.1). If the adjusted p-value cutoff (FDR) will be a value other than 0.1, alpha should be set to that value. This argument will be passed to results. |
independentFiltering |
logical, whether independent filtering should be
applied automatically. By default it's set to |
filter |
the vector of filter statistics over which the independent filtering
will be optimized. By default the logCPM will be used if
|
theta |
the quantiles at which to assess the number of rejections from independent filtering. This argument is passed results. |
filterFun |
an optional custom function as described in results. |
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 |
device |
The graphical device used when knitting. See more at
http://yihui.name/knitr/options ( |
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 |
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 |
... |
Arguments passed to other methods and/or advanced arguments. Advanced arguments:
|
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.
If you modify the YAML front matter of template
, you can use other
values for output_format
.
This report is similar to the one created by DESeq2Report with two additional plots exclusive for edgeR results. We designed the reports to be very similar intentionally and use the Bioconductor package DEFormats to achieve this goal.
An HTML report with a basic exploration for the given set of edgeR results. See the example report at http://leekgroup.github.io/regionReport/reference/edgeReport-example/edgeRexploration.html.
Leonardo Collado-Torres
## Create example data using DEFormats
library("DEFormats")
set.seed(20160407)
counts <- simulateRnaSeqData()
group <- rep(c("A", "B"), each = 3)
## Create DGEList object
library("edgeR")
dge <- DGEList(counts, group = group)
## Perform DE analysis with edgeR
design <- model.matrix(~group)
dge <- estimateDisp(dge, design)
fit <- glmFit(dge, design)
lrt <- glmLRT(fit, coef = 2)
## The output will be saved in the 'edgeReport-example' directory
dir.create("edgeReport-example", showWarnings = FALSE, recursive = TRUE)
## Generate the HTML report
report <- edgeReport(dge, lrt,
project = "edgeR-example", intgroup = "group",
outdir = "edgeReport-example"
)
if (interactive()) {
## Browse the report
browseURL(report)
}
## See the example report at
## http://leekgroup.github.io/regionReport/reference/edgeReport-example/edgeRexploration.html
## Not run:
## Note that you can run the example using:
example("edgeReport", "regionReport", ask = FALSE)
## End(Not run)
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