MultiRNAflow

Introduction

The MultiRNAflow package is aimed at biologists and bioinformaticians who wish to automatically analyze RNAseq datasets with multiple times and/or multiple biological conditions. The MultiRNAflow suite gathers in a unified framework methodological tools found in various existing packages allowing to perform:

1. Exploratory (unsupervised) analysis of the data.
2. Statistical (supervised) analysis of dynamic transcriptional expression (DE genes), based on DESeq2 R package.
3. Functional and GO analysis of subsets of genes automatically selected by the package, such as specific genes or genes with a given DE temporal pattern.

The package automates a commonly used workflow of analysis for studying complex biological phenomena.

Our package takes as input a transcriptional dataset with an experimental design that includes multiple groups of individuals and/or multiple times, t0 (reference time) and ti (1 $\leq$ i $\leq$ n). The dataset is a table of raw counts where lines correspond to genes and columns correspond to samples. Each sample show the raw counts of an individual sequencing, corresponding to a biological condition, an individual sampling in this biological condition and a time.

Installation

Before installing the necessary packages, you must install (or update) the R software in a version superior or equal to 4.2.1 “Funny-Looking Kid” (released on 2022/06/23) from .

Then, in order to use the MultiRNAflow package, the following R packages must be installed:

• From CRAN repository: reshape2 (>= 1.4.4), ggplot2 (>= 3.4.0), ggalluvial (>= 0.12.3), ggrepel (>= 0.9.2), FactoMineR (>= 2.6), factoextra (>= 1.0.7), plot3D (>= 1.4), plot3Drgl (>= 1.0.3), ggplotify (>= 0.1.2), UpSetR (>= 1.4.0), gprofiler2 (>= 0.2.1)
• From CRAN repository and usually already included by default in R: graphics (>= 4.2.2), grDevices (>= 4.2.2), grid (>= 4.2.2), utils (>= 4.2.2), stats (>= 4.2.2).
• From Bioconductor repository: SummarizedExperiment (>= 1.28.0), DESeq2 (>= 1.38.1), ComplexHeatmap (>= 2.14.0), Mfuzz (>= 2.58.0).

Before installing a package, for instance the package FactoMineR, the user must check if the package is already installed with the command . If the package has not been previously installed, the user must use the command (packages from CRAN). For beginners in programming, we recommend to follow the steps below for importing CRAN and Bioconductor packages.

For the packages which must be download from CRAN,

Cran.pck <- c("reshape2", "ggplot2", "ggrepel", "ggalluvial",
              "FactoMineR", "factoextra",
              "plot3D", "plot3Drgl", "ggplotify", "UpSetR", "gprofiler2")

the user can copy and paste the following lines of code for each package in order to download the missing packages.

Select.package.CRAN <- "FactoMineR"
if (!require(package=Select.package.CRAN,
             quietly=TRUE, character.only=TRUE, warn.conflicts=FALSE)) {
    install.packages(pkgs=Select.package.CRAN, dependencies=TRUE)
}

If the package is already installed (for instance here FactoMineR), the previous lines of code will return nothing.

For the packages which must be download from Bioconductor,

Bioconductor.pck <- c("SummarizedExperiment", "S4Vectors", "DESeq2",
                      "Mfuzz", "ComplexHeatmap")

the user must first copy and paste the following lines of code in order to install BiocManager

if (!require(package="BiocManager",
             quietly=TRUE, character.only=TRUE, warn.conflicts=FALSE)) {
    install.packages("BiocManager")
}# if(!require(package="BiocManager", quietly=TRUE, character.only=TRUE))

then copy and paste the following lines of code in order to install the version 3.18 of Bioconductor (it works with R version 4.2.0)

BiocManager::install(version="3.18")

and then copy and paste the following lines of code for each package in order to download the missing packages.

Select.package.Bioc <- "DESeq2"
if (!require(package=Select.package.Bioc,
             quietly=TRUE, character.only=TRUE, warn.conflicts=FALSE)) {
    BiocManager::install(pkgs=Select.package.Bioc)
}

If the package is already installed (for instance here DESeq2), the previous lines of code will return nothing.

Once all packages have been installed, the user may load our package.

## BiocManager::install(pkgs="MultiRNAflow") ## to install
library(MultiRNAflow)