diff --git a/R/ChIPuana-package.r b/R/ChIPflow-package.r
similarity index 80%
rename from R/ChIPuana-package.r
rename to R/ChIPflow-package.r
index b965eb2a1a2c180d10e85ac7b8b18c547eded68d..11d715f25e9f931741b458db9dada551bf1e3e88 100755
--- a/R/ChIPuana-package.r
+++ b/R/ChIPflow-package.r
@@ -1,6 +1,6 @@
 #' Provide R tools and an environment for the statistical analysis of ChIP-Seq data: load and clean data, produce figures, perform statistical analysis/testing with DESeq2 or edgeR, export results and create final report
-#' @title Statistical Analysis of RNA-Seq Tools
+#' @title Statistical Analysis of ChIP-Seq Tools
 #' @author Maelle Daunesse, Marie-Agnes Dillies and Hugo Varet
 #' @docType package
-#' @name ChIPuana-package
+#' @name ChIPflow-package
 NULL
diff --git a/R/welcome.R b/R/welcome.R
index 0f31a6c18a66ed89ddce514869317939f912cac5..3ddf1b466740e559640845698cb9423480fecd44 100755
--- a/R/welcome.R
+++ b/R/welcome.R
@@ -3,7 +3,7 @@
 # ==========================================================================
 .onAttach = function(libname, pkgname) {
   msg <- c("----------------------------------------------",
-          paste0("Welcome to ChIPuanaR version ", packageVersion("ChIPuanaR")))
+          paste0("Welcome to ChIPflowR version ", packageVersion("ChIPflowR")))
   msg <- c(msg,"----------------------------------------------")
   msg <- strwrap(msg, exdent=4, indent=4)
   packageStartupMessage(paste(msg, collapse="\n"), appendLF=TRUE)
diff --git a/README.md b/README.md
index 5e9610ab4f866a7d6625cad6fccc9856c74483d1..abebf4ac23bf6ac9422792ee27d184ccaa601dfb 100644
--- a/README.md
+++ b/README.md
@@ -1,11 +1,11 @@
-# ChIPuanaR
+# ChIPflowR
 
-How to install ChIPuanaR?
+How to install ChIPflowR?
 -------------------------
 
-In addition to the ChIPuanaR package itself, the workflow requires the installation of several packages: DESeq2, limma, knitr... (all available online, see the dedicated webpages).
+In addition to the ChIPflowR package itself, the workflow requires the installation of several packages: DESeq2, limma, knitr... (all available online, see the dedicated webpages).
 
-To install the ChIPuanaR package from GitLab, open a R session and:
+To install the ChIPflowR package from GitLab, open a R session and:
 - Install devtools with `install.packages("devtools")` (if not installed yet)
 - Notes:
 
@@ -13,4 +13,4 @@ To install the ChIPuanaR package from GitLab, open a R session and:
 	- Some users may have to install the pandoc and pandoc-citeproc libraries to be able to generate the final HTML reports
 
 - For Windows users only, install [Rtools](https://cran.r-project.org/bin/windows/Rtools/) or check that it is already installed (needed to build the package)
-- Run `devtools::install_gitlab(repo="hub/chipuanar", host="gitlab.pasteur.fr", build_vignettes=TRUE)`
+- Run `devtools::install_gitlab(repo="hub/chipflowr", host="gitlab.pasteur.fr", build_vignettes=TRUE)`
diff --git a/inst/Report_ChIPuanaR.Rmd b/inst/Report_ChIPflowR.Rmd
similarity index 96%
rename from inst/Report_ChIPuanaR.Rmd
rename to inst/Report_ChIPflowR.Rmd
index db1962ad04448990b91fb81d4daa1c066809f9a8..72f9a899e7034f234a460b169bbd3411e6d8f4f5 100644
--- a/inst/Report_ChIPuanaR.Rmd
+++ b/inst/Report_ChIPflowR.Rmd
@@ -1,10 +1,10 @@
 ---
-#logopath: "inst/Logos_LogoC3BI.png" #system.file("Logos_LogoC3BI.png", package = "ChIPuana")
-title: "ChIPuana differential analysis report"
+#logopath: "inst/Logos_LogoC3BI.png" #system.file("Logos_LogoC3BI.png", package = "ChIPflow")
+title: "ChIPflow differential analysis report"
 date: '`r Sys.Date()`'
 output:
   html_document:
-    #css: ""#system.file("vignette.css", package = "ChIPuana")
+    #css: ""#system.file("vignette.css", package = "ChIPflow")
     toc: TRUE
     toc_depth: 2
     toc_float:
@@ -18,15 +18,14 @@ bibliography: bibliography.bib
 csl: medecine-sciences.csl
 ---
 
-This report is generated by ChIPuanaR, and R package included in ChIPuana a Snakemake pipeline for ChIP-seq data. ChIPuanar is an adaptation of the SARTools R package [@Varet2016] and is freely available at https://gitlab.pasteur.fr/hub/chipuanar. If you use ChIPuana and/or ChIPuanaR please cite: M. Daunesse, R Legendre, H. Varet, A. Pain, C. Chica. 2021. _ChIPuana: from raw data to epigenomic dynamics_, bioRxiv.
+This report is generated by ChIPflowR, and R package included in ChIPflow a Snakemake pipeline for ChIP-seq data. ChIPflowR is an adaptation of the SARTools R package [@Varet2016] and is freely available at https://gitlab.pasteur.fr/hub/chipflowr. If you use ChIPflow and/or ChIPflowR please cite: M. Daunesse, R Legendre, H. Varet, A. Pain, C. Chica. 2021. _ChIPflow: from raw data to epigenomic dynamics_, bioRxiv.
 
 ```{r echo=FALSE, results="asis", results="hide", message=FALSE, warning=FALSE}
 # Package
 library(knitr)
 library(kableExtra)
-library(ChIPuanaR)
+library(ChIPflowR)
 ### INPUTS
-# setwd("~/work/projects/ChIPuana/chipuanar/inst")
 source("config.R")
 data <- read.table(file = file, header=TRUE)
 counts <- as.matrix(data[,-c(1:6)])
@@ -83,7 +82,7 @@ for (name in names(resAnDif$results)){
 
 # 1. Introduction
 
-The differential analysis is performed to detect differentially marked/bound peaks between the biological conditions. Two approaches to model variability (DESeq2 and limma) as well as linear and nonlinear normalisation methods (scalar, quantile, cyclicloess, spike-in) are available to perform the DA. Using the count matrix generated by featureCounts, ChIPuanaR allows to carry out the quality assessment of the data using dedicated plots, to run the DA and to export (i) a Rmarkdown HTML report describing the analysis process and (ii) the tables containing the differentially marked/bound peaks. 
+The differential analysis is performed to detect differentially marked/bound peaks between the biological conditions. Two approaches to model variability (DESeq2 and limma) as well as linear and nonlinear normalisation methods (scalar, quantile, cyclicloess, spike-in) are available to perform the DA. Using the count matrix generated by featureCounts, ChIPflowR allows to carry out the quality assessment of the data using dedicated plots, to run the DA and to export (i) a Rmarkdown HTML report describing the analysis process and (ii) the tables containing the differentially marked/bound peaks. 
 
 # 2. Description of raw data
 
diff --git a/man/ChIPuana-package.Rd b/man/ChIPflow-package.Rd
similarity index 70%
rename from man/ChIPuana-package.Rd
rename to man/ChIPflow-package.Rd
index 85e9f42b4e2ae76b4ee336a4a949919bbf8ef16c..8dfa78a29e6978f010a1247ae5042776966f0b57 100644
--- a/man/ChIPuana-package.Rd
+++ b/man/ChIPflow-package.Rd
@@ -1,9 +1,9 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/ChIPuana-package.r
+% Please edit documentation in R/ChIPflow-package.r
 \docType{package}
-\name{ChIPuana-package}
-\alias{ChIPuana-package}
-\title{Statistical Analysis of RNA-Seq Tools}
+\name{ChIPflow-package}
+\alias{ChIPflow-package}
+\title{Statistical Analysis of ChIP-Seq Tools}
 \description{
 Provide R tools and an environment for the statistical analysis of ChIP-Seq data: load and clean data, produce figures, perform statistical analysis/testing with DESeq2 or edgeR, export results and create final report
 }