Commit 1f2924e4 authored by Sudeep Sahadevan's avatar Sudeep Sahadevan

BiocCheck 2 failures

parent 613c078b
......@@ -3,35 +3,26 @@ Type: Package
Title: Differential Expressed Windows Based on Negative Binomial Distribution
Version: 1.6.0
Authors@R: c(
person("Sudeep", "Sahadevan", email="sahadeva@embl.de", role = c("aut","cre")),
person("Thomas", "Schwarzl", email="schwarzl@embl.de", role = c("aut", "ctb"))
person("Sudeep", "Sahadevan", email="sahadeva@embl.de", role = c("cre")),
person("Thomas", "Schwarzl", email="schwarzl@embl.de", role = c("ctb"))
)
Maintainer: Hentze bioinformatics team <biohentze@embl.de>
Description: Differential expression analysis of windows for next-generation sequencing data like eCLIP or iCLIP data.
Imports:
DESeq2,
BiocGenerics,
BiocParallel,
data.table,
GenomeInfoDb,
GenomicRanges,
methods,
S4Vectors,
SummarizedExperiment,
stats,
utils
Depends:
DESeq2,
BiocGenerics,
BiocParallel,
data.table,
GenomeInfoDb,
GenomicRanges,
methods,
S4Vectors,
SummarizedExperiment,
utils
BiocParallel
Suggests:
knitr,
knitr,
rmarkdown
VignetteBuilder:
knitr
......
......@@ -19,4 +19,4 @@ BuildType: Package
PackageUseDevtools: Yes
PackageInstallArgs: --no-multiarch --with-keep.source
PackageCheckArgs: --as-cran
PackageRoxygenize: rd,collate,namespace
PackageRoxygenize: rd,collate,namespace,vignette
......@@ -57,6 +57,13 @@
#' @param log2FoldChangeThresh threshold for log2foldchange value (default:1)
#' @param begin0based TRUE (default) or FALSE. If TRUE, then the start positions in \code{windowRes} is considered to be 0-based
#'
#' @examples
#' # need specific examples
#' \dontrun{
#' 'regionRes <- extractRegions(windowRes)'
#' }
#'
#'
#' @return data.frame
extractRegions <- function(windowRes,
padjCol = 'padj',
......
......@@ -68,6 +68,12 @@
#' @param minmu lower bound on the estimated count (used when calculating contrasts)
#' @param begin0based TRUE (default) or FALSE. If TRUE, then the start positions in \code{annotationFile} are considered to be 0-based
#'
#' @examples
#' # need specific examples
#' \dontrun{
#' 'windowRes <- resultsDEWSeq(object=dds,annotationFile="/path/to/annotation.gz")'
#' }
#'
#' @return data.frame
resultsDEWSeq <- function(object, annotationFile,
contrast,name,
......
......@@ -5,7 +5,8 @@
#' @title windows/regions to BED
#' @description given output of \code{\link{extractRegions}}, \code{\link({resultsDEWSeq}} and significance thresholds,
#' extract significant windows, create regions by merging adjacent significant windows.
#' Finally, write the output as a BED file for visualization
#' Finally, write the output as a BED file for visualization.
#'
#' @param windowRes output data.frame from \code{\link{resultsDEWSeq}}
#' @param regionRes output data.frame from \code{\link{extractRegions}}
#' @param fileName filename to save BED output
......@@ -15,6 +16,13 @@
#' @param log2FoldChangeThresh threshold for log2foldchange value (default:1)
#' @param trackName name of this track, for visualization
#' @param description description of this track, for visualization
#'
#' @examples
#' # need specific examples
#' \dontrun{
#' 'toBED(windowRes=windowRes,regionRes=regionRes,fileName="enrichedWindowsRegions.bed")'
#' }
#'
#' @return NULL
toBED <- function(windowRes,regionRes,fileName,padjCol='padj',padjThresh=0.05,log2FoldChangeCol='log2FoldChange',log2FoldChangeThresh=1,trackName='sliding windows',
description='sliding windows'){
......
......@@ -70,6 +70,13 @@
#' @param op can be one of \code{max} (default) or \code{min}. \code{max} returns windows with maximum log2FoldChange and mean normalized expression in the \code{treatmentCols} columns,
#' \code{min} returns windows with minimum log2FoldChange and mean normalized expression
#'
#'
#' @examples
#' # need specific examples
#' \dontrun{
#' 'topWindoPerRegionStats <- topWindowStats(windowRes=windowRes,normalizedCount=normCount)'
#' }
#'
#' @return data.frame
topWindowStats <- function(windowRes,padjCol='padj',padjThresh=0.05,log2FoldChangeCol='log2FoldChange',log2FoldChangeThresh=1,begin0based=TRUE, normalizedCounts,
treatmentCols,treatmentName='treatment',controlName='control', op='max'){
......
......@@ -64,3 +64,11 @@ The output data.frame from this function will have the following columns:
\item \code{log2FoldChange_mean}: average log 2 fold change in the region
}
}
\examples{
# need specific examples
\dontrun{
'regionRes <- extractRegions(windowRes)'
}
}
......@@ -84,3 +84,10 @@ columns:\cr
\code{pvalue}, \code{padj}. Please consult DESeq2 vignettes for an
explanation of these columns.
}
\examples{
# need specific examples
\dontrun{
'windowRes <- resultsDEWSeq(object=dds,annotationFile="/path/to/annotation.gz")'
}
}
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/toBED.R
\name{toBED}
\alias{toBED}
\title{windows/regions to BED}
\usage{
toBED(windowRes, regionRes, fileName, padjCol = "padj",
padjThresh = 0.05, log2FoldChangeCol = "log2FoldChange",
log2FoldChangeThresh = 1, trackName = "sliding windows",
description = "sliding windows")
}
\arguments{
\item{windowRes}{output data.frame from \code{\link{resultsDEWSeq}}}
\item{regionRes}{output data.frame from \code{\link{extractRegions}}}
\item{fileName}{filename to save BED output}
\item{padjCol}{name of the adjusted pvalue column (default: padj)}
\item{padjThresh}{threshold for p-adjusted value (default: 0.05)}
\item{log2FoldChangeCol}{name of the log2foldchange column (default: log2FoldChange)}
\item{log2FoldChangeThresh}{threshold for log2foldchange value (default:1)}
\item{trackName}{name of this track, for visualization}
\item{description}{description of this track, for visualization}
}
\description{
given output of \code{\link{extractRegions}}, \code{\link({resultsDEWSeq}} and significance thresholds,
extract significant windows, create regions by merging adjacent significant windows.
Finally, write the output as a BED file for visualization.
}
\examples{
# need specific examples
\dontrun{
'toBED(windowRes=windowRes,regionRes=regionRes,fileName="enrichedWindowsRegions.bed")'
}
}
......@@ -86,3 +86,10 @@ The output data.frame of this function has the following columns:
\item the next columns will be normalized expression values of the meanWindow from individual treatment and control samples
}
}
\examples{
# need specific examples
\dontrun{
'topWindoPerRegionStats <- topWindowStats(windowRes=windowRes,normalizedCount=normCount)'
}
}
## ----setup, echo=FALSE, results="hide"-----------------------------------
# DEWSeq package version: `r packageVersion("DESeq2")` <- this goes into abstract
knitr::opts_chunk$set(tidy=FALSE, cache=FALSE,
dev="png",
message=FALSE, error=FALSE, warning=TRUE)
## ---- eval = F, echo = F-------------------------------------------------
# #**Note:** if you use DEWSeq in published research, please cite:
# #
# #> Authors. (Year)
# #> Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.
# #> *Genome Biology*, **15**:550.
# #> [10.1186/s13059-014-0550-8](http://dx.doi.org/10.1186/s13059-014-0550-8)
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