%\VignetteIndexEntry{DEGreport}
%\VignetteKeywords{DifferentialExpression, Visualization, RNASeq, ReportWriting}
%\VignetteEngine{knitr::knitr}

\documentclass[12pt]{article}

\newcommand{\deseqtwo}{\textit{DESeq2}}
\newcommand{\lowtilde}{\raise.17ex\hbox{$\scriptstyle\mathtt{\sim}$}}

<<knitr, echo=FALSE, results="hide">>=
library("knitr")
opts_chunk$set(tidy=FALSE,dev="png",fig.show="hide",
               fig.width=4,fig.height=4.5,
               message=FALSE)
@


<<style, eval=TRUE, echo=FALSE, results="asis">>=
BiocStyle::latex()
@

\title{DEGreport }
\author{Lorena Pantano}
\date{Modified: 23 May, 2014. Compiled: \today}

\begin{document}

\maketitle



<<package-load,message=FALSE>>=
library(DEGreport)
data(humanSexDEedgeR)
library(edgeR)
@


We are going to do a differential expression analysis with edgeR. We have an
object that is comming from the edgeR package. It countains a gene count matrix
for 85 TSI HapMap individuals, and the gender information. With that, we are
going to apply the `glmFit` function to get genes differentially expressed
between males and females.

<<chunk-1>>=
des<-humanSexDEedgeR$design
fit <- glmFit(humanSexDEedgeR,des)
lrt <- glmLRT(fit)
tab<-cbind(lrt$table,p.adjust(lrt$table$PValue,method="BH"))
detags <- rownames(tab[tab[,5]<=0.1,])
plotSmear(humanSexDEedgeR, de.tags=detags)
@

We need to extract the experiment design data.frame where the condition is
Male or Female.

<<chunk-2>>=
counts<-cpm(humanSexDEedgeR,log=FALSE)
g1<-colnames(counts)[1:41]
g2<-colnames(counts)[42:85]
design<-data.frame(condition=sub("1","Male",sub("0","Female",des[,2])))
@

We are getting the chromosome information for each gene. This way we can colour
genes according autosomic,X or Y chromosomes.

<<chunk-3>>=
data(geneInfo)
@

Create the report. The main parameters are the column names in group1, and
group2. Then, the count matrix, gene names that are DE, p-values, fold changes
and path to create the report. As optional, you can give colours for each gene,
and the number of permutation.

<<chunk-4>>=
detag10<-detags[1:10]
pval<-tab[,4]
fc<-tab[detag10,1]
@
Run the following lines to create the file

<<chunk-5, eval=FALSE>>=
pathreport<-"~/report" #change this to a proper path
createReport(g1,g2,counts,detag10,pval,fc,pathreport,colors,pop=400)
@

Run the fowlling lines if you want to visualize your expression values by
condition:

<<chunk-6, eval=FALSE>>=
degObj(counts,design,"/tmp/degObj.rda")
library(shiny)
runGist(9930881)
@

You can use individual functions, like degRank or degMean. This will create
specific figures and tables that are included in the report.

<<chunk-7>>=
degMean(pval,counts)
degVar(pval,counts)
degMV(g1,g2,pval,counts)
degMB(detags,g1,g2,counts)
degVB(detags,g1,g2,counts)
@

<<chunk-8, eval=FALSE>>==
library(coda)
library(rjags)
rank<-degRank(g1,g2,counts[detag10,],fc,400,500)
degPR(rank)
@

\end{document}