Rna sequence analysis4/16/2023 ![]() The concept of dual RNA-seq can be further extended: triple RNA-seq allows investigating the interaction of three organisms, e. The special variant dual RNA-seq can be applied to analyse the transcriptome of two interacting species at the same time by separating their RNA in silico ( Schulze et al., 2016 Wolf et al., 2018). In fact, interspecies interactions are a major part of environmental adaptation. However, species do not exist in isolation. RNA sequencing (RNA-seq) offers a complete, fast, and cheap way to perform transcriptomics of single organisms using next-generation-sequencing technologies ( Mardis, 2008). The primary goal is the detection of genes whose expression changes significantly between two or more conditions, and the function relationship of these genes. With the help of transcriptomics scientists are able to study the gene expression of a given organism allowing to get insights in the interplay of genes dependent on environmental alterations. Organisms constantly change the expression of their genes to adapt to changes in the environment. GEO2RNAseq is publicly available at and, including source code, installation instruction, and comprehensive package documentation. GEO2RNAseq is implemented in R, lightweight, easy to install via Conda and easy to use, but still very flexible through using modular programming and offering many extensions and alternative workflows. GEO2RNAseq strongly incorporates experimental as well as computational metadata. Raw data may be provided in FASTQ format or can be downloaded automatically from the Gene Expression Omnibus repository. It covers all pre-processing steps starting from raw sequencing data to the analysis of differentially expressed genes, including various tables and figures to report intermediate and final results. In this publication we present the “GEO2RNAseq” pipeline for complete, quick and concurrent pre-processing of single, dual, and triple RNA-seq data. The analysis of RNA-seq can be simplified as many steps of the data pre-processing can be standardised in a pipeline. The primary goal is the detection of genes whose expression changes significantly between two or more conditions, either for a single species or for two or more interacting species at the same time (dual RNA-seq, triple RNA-seq and so forth). In transcriptomics, the study of the total set of RNAs transcribed by the cell, RNA sequencing (RNA-seq) has become the standard tool for analysing gene expression. ![]()
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