---
title: "Log-Linear Poisson Graphical Model with Hot-Deck Multiple Imputation"
author:
- affiliation: MIAT, Université de Toulouse, INRA, Castanet-Tolosan, France
  name: Nathalie Villa-Vialaneix
- affiliation: MIAT, Université de Toulouse, INRA, Castanet-Tolosan, France
  name: Alyssa Imbert
output:
  html_document:
    toc: yes
  pdf_document:
    toc: yes
package: RNAseqNet
abstract: |
  Short vignette pointing to RNAseqNet User's Guide.
vignette: |
  %\VignetteIndexEntry{Log-Linear Poisson Graphical Model with Hot-Deck Multiple Imputation}
  %\VignetteEncoding{UTF-8}
  %\VignetteEngine{knitr::rmarkdown}
---


# Description

The **R** package `RNAseqNet` can be used to infer networks from RNA-seq 
expression data. The count data are given as a $n \times p$ matrix in which $n$ 
is the number of individuals and $p$ the number of genes. This matrix is denoted
by $\mathbf{X}$ in the sequel.

Eventually, the RNA-seq dataset is complemented with an $n' \times d$ matrix, 
$\mathbf{Y}$ which can be used to impute missing individuals in $\mathbf{X}$
as described in [Imbert *et al.*, 2018].

The RNAseqNet User's Guide can be opened with:
```{r PDF, eval=FALSE}
RNAseqNetUsersGuide()
```

The location of the source file is given by:
```{r Rmd, eval=FALSE}
RNAseqNetUsersGuide(html = FALSE)
```


# Reference

Imbert, A., Valsesia, A., Le Gall, C., Armenise, C., Lefebvre, G., Gourraud, 
P.A., Viguerie, N. and Villa-Vialaneix, N. (2018) Multiple hot-deck imputation 
for network inference from RNA sequencing data. *Bioinformatics*. 
DOI: http://dx.doi.org/10.1093/bioinformatics/btx819.


