An R package for analysing RNA-seq raw counts with several biological conditions and different time points

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Documentation for package ‘MultiRNAflow’ version 1.0.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

CharacterNumbers	Transformation of a vector of integers into a vector of class "character".
ColnamesToFactors	Extraction of factors information and suitable column names creation from the column names of a dataset.
DATAnormalization	Normalization of raw counts (Main Function).
DATAplotBoxplotSamples	Visualization of the distribution of all gene expressions using a boxplot for each sample.
DATAplotExpression1Gene	Plot expression of one gene.
DATAplotExpressionGenes	Plot expression of a subset of genes.
DATAprepSE	Data preparation for exploratory and statistical analysis (Main Function)
DEanalysisGlobal	Realization of the DE analysis (Main Function).
DEanalysisGroup	DE Analysis when samples belong to different biological conditions.
DEanalysisSubData	Sub data of a data.frame
DEanalysisTime	DE analysis when samples belong to different time points only.
DEanalysisTimeAndGroup	DE analysis when samples belong to different biological condition and time points.
DEplotAlluvial	Alluvial graphs of differentially expressed (DE) genes
DEplotBarplot	Barplot of DE genes from a contingency table.
DEplotBarplotFacetGrid	Faceted barplot of specific DE genes
DEplotBarplotTime	Barplot of DE genes per time
DEplotHeatmaps	Heatmaps of DE genes
DEplotVennBarplotGroup	Venn barplot of DE genes across pairs of biological conditions.
DEplotVennBarplotTime	Venn barplot of DE genes across time.
DEplotVolcanoMA	Volcano and MA graphs
DEresultGroup	Intermediate analysis when samples belong to different biological conditions
DEresultGroupPerTime	Intermediate analysis when samples belong to different biological conditions and different time points.
GSEApreprocessing	GSEA preprocessing for official software and online tools.
GSEAQuickAnalysis	GSEA analysis with gprofiler2
HCPCanalysis	Hierarchical clustering analysis with HCPC (Main function)
MFUZZanalysis	Clustering of temporal patterns (Main function).
MFUZZclustersNumber	Automatic choice of the number of clusters to use for the Mfuzz analysis
PCAanalysis	Automatic PCA analysis (Main function)
PCAgraphics	Multiple 2D and 3D PCA graphs.
PCApreprocessing	Reshaped dataset for factorial analysis.
PCArealization	PCA realization
RawCountsSimulation	RNA-seq raw counts data simulation
RawCounts_Antoszewski2022_MOUSEsub500	Mouse raw counts data
RawCounts_Leong2014_FISSIONsub500wt	Yeast times series raw counts data after stimulation with and without silencing
RawCounts_Schleiss2021_CLLsub500	Human CCL times series raw counts data after stimulation with and without silencing
RawCounts_Weger2021_MOUSEsub500	Mouse count data with four biological conditions, six time measurements and 500 genes.
Results_DEanalysis_sub500	DE results of three dataset